Excel Ai Agent Jobs in Usa

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• A typical day will involve a mix of hands-on coding, architectural design, and research.
  
• The engineer will spend a significant portion of their time in Python, building and optimizing agentic AI systems using frameworks like LangChain.
  
• This includes integrating these agents with our backend services and deploying them using CI/CD pipelines into our cloud environment.
  
• They will also be responsible for researching and testing new agentic models and frameworks, monitoring agent behavior in production, and collaborating with data scientists and business stakeholders to refine requirements and ensure the ethical deployment of AI solutions.
  

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• Python
  
• JavaScript/TypeScript
  
• AI Tools and Libraries (e.g. LangGraph, LangChain, Deep Agents, Claude Skills, etc.)
  
• AI Models (e.g. Claude, OpenAI, etc.)
  
• AI Concepts (e.g. Prompt Engineering, RAG, Agentic AI, etc.)
  
• Distributed SDLC/DevOps (e.g. github, pipelines, VS Code, testing frameworks, etc.)
  
• Platforms (Container Platforms, Cloud Platforms, Document Databases, AWS)
  
• API Design
  

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• Deep hands-on experience in Python for AI/ML development.
  

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• Generative AI Development: Proven experience developing Gen AI or AI/ML solutions, from use case conceptualization to production deployment.
  
• Infrastructure & DevOps: Strong understanding of cloud environments (AWS preferred), LLM hosting, CI/CD pipelines, Docker, and Kubernetes.
  
• Agentic AI Concepts: Knowledge of agentic/autonomous systems (e.g., reasoning, planning, tool use).
  

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• Proficiency in Python development and FastAPI/Flask frameworks, along with SQL.
  
• Familiarity with agentic AI frameworks and concepts such as LangChain, LangGraph, AutoGen, Model Context Protocol (MCP), Chain of Thought prompting, knowledge stores, and embeddings.
  
• Experience developing autonomous agents using cloud-based AI services.
  
• Experience with prompt engineering techniques and model fine-tuning.
  
• Strong understanding of reinforcement learning, planning algorithms, and multi-agent systems.
  
• Experience working across cloud platforms (AWS, Azure, GCP) and deploying AI solutions at scale.
  

Location: Seattle (in-person)

Salary: $70,000–$110,000 depending on experience

Nimbus AI builds the fastest way for companies to create, train, and resell branded conversational and workflow agents. Our platform automates data capture, optimization, and deployment so teams can transform conversations and workflows into continuously improving, revenue-generating AI products.

We're hiring a QA Manager to build and lead the quality assurance function for Nimbus's agentic AI systems. You'll establish testing frameworks, develop evaluation criteria, and ensure our conversational agents and workflow automations perform reliably across all customer deployments. You'll work cross-functionally with product, engineering, and customer teams to catch edge cases, validate model behavior, and maintain the quality standards that make Nimbus agents trustworthy at scale.

This role is perfect for someone who loves building QA processes from the ground up, has a sharp eye for AI-specific failure modes, and can translate ambiguous agent behaviors into concrete test cases and quality metrics.

• QA strategy & framework development for conversational agents, workflow automations, and partner-specific models across multiple verticals.
• Test planning and execution—designing test cases, evaluation rubrics, regression suites, and automated testing pipelines for agent behavior.
• Quality metrics and monitoring to track agent accuracy, consistency, guardrail effectiveness, and performance degradation over time.
• Cross-functional collaboration with prompt engineers, product, and engineering teams to identify, document, and resolve quality issues.
• Agent validation processes to ensure new releases, prompt changes, and training updates maintain reliability standards.
• Team building and leadership as we scale—hiring, mentoring, and growing the QA function.

• 5+ years of QA experience, with at least 2 years in a management or lead role.
• Experience testing AI/ML products, LLM applications, or conversational systems—you understand non-deterministic behavior and how to test it.
• Strong analytical skills—comfortable evaluating agent outputs, identifying patterns in failures, and defining measurable quality standards.
• Ability to build testing frameworks from scratch, including test case libraries, evaluation criteria, and automation strategies.
• Experience with technical testing tools (APIs, JSON, test automation frameworks, monitoring systems).
• Excellent communication skills—you can clearly document bugs, write test plans, and explain quality issues to technical and non-technical stakeholders.
• Leadership experience building or managing QA teams, processes, and culture.

• Build the QA function from the ground up—define how quality works for agentic AI at scale.
• Be part of a small, fast team where your quality standards will directly impact hundreds of deployed agents.
• Work with cutting-edge LLMs and agentic systems—testing challenges that don't exist anywhere else yet.
• Grow into a senior leadership role as our platform, customer base, and team expand.

Profitmind is building the intelligence behind how retailers make pricing and merchandising decisions. Today, many of these decisions are still driven by spreadsheets, rigid rules, and manual judgment, even at the largest brands.

Our platform turns complex data such as sales, inventory, and competitive signals into clear, explainable recommendations merchants can trust. Our platform focuses on impact, helping retailers improve margin, inventory health, and decision quality at scale. 

Based in Pittsburgh, Profitmind is backed by a recent strategic investment from Accenture, and scaling its agentic AI platform to power decision-making for some of the world’s largest retailers.

About the role:

We’re looking for a multi-disciplinary AI Engineer to design, implement, and deploy LLM-driven agents with strong backend and front-end integration. You’ll be leading efforts across LLM agent design, prompting, fine-tuning, and MLOps, while building real-world, production-grade applications with modern web technologies.

The ideal candidate combines a strong foundation in Python and AI with practical experience in agent frameworks like LangGraph, PydanticAI, and Google ADK, as well as FastAPI and front-end development.

What you’ll do:

LLM Agents & Prompt Engineering

• Architect and implement LLM agents using frameworks like LangGraph, PydanticAI, and Google ADK.
• Build composable, tool-augmented reasoning chains (e.g., RAG, CoT, ReAct, planner-executor).
• Integrate vector databases (e.g., FAISS, Pinecone, pgvector) and knowledge graphs (Neo4j) to support retrieval-augmented generation (RAG) and long-term chatbot memory.
• Design and maintain high-quality prompt strategies for robustness and reliability.

FastAPI, Model Context Protocol (MCP) & Backend

• Develop and maintain scalable APIs using FastAPI, supporting synchronous and asynchronous agent execution.
• Integrate Model Context Protocol (MCP) to enable secure and structured access to external data and tools within agent workflows.
• Implement state tracking, context-aware input dispatch, and modular plugin integration within the control plane.

Evaluation, Testing & Observability

• Build unit and behavioral tests for agents, tools, and workflows.
• Develop tooling for trace analysis, agent state debugging, and hallucination tracking.
• Compare and benchmark agent orchestration frameworks for trade-offs in speed, reliability, and usability.

Model Fine-Tuning & MLOps

• Fine-tune models using LoRA, QLoRA, or full fine-tuning pipelines.
• Integrate, deploy, and monitor models in production using cloud providers.
• Set up agent logging, observability dashboards, and recovery workflows.

Front-End & UX

• Familiar with React, TypeScript, Next.js, or similar frameworks
• Understanding of front-end and back-end integration for AI tools
• Ability to build basic dashboards or agent interfaces
• Integrate agents into interfaces
• Speak the language of UI 

What we’re looking for:

• 3+ years experience with Python in ML/AI systems and PyTorch or Tensorflow
• 1+ years experience with LLM agent development, prompt engineering, and frameworks like
• LangGraph, PydanticAI, and Google ADK.
• Experience with fine-tuning LLMs.
• Familiarity using vector stores like ChromaDB, Weaviate, or pgvector.
• Production experience with FastAPI, Docker, and MLOps
• Expert in Agentic Coding IDEs (Windsurf, Cursor or Claude Code)
• Bachelor’s or Master's degree in computer science

Nice to have:

• Open-source contributions to LLM/agent tooling
• Knowledge of async programming, websockets, and streaming APIs

What we offer:

• Competitive compensation and equity
• Comprehensive benefits including medical, dental, vision, etc.
• Unlimited and flexible PTO

Location: Anywhere in Country

At EY, we’re all in to shape your future with confidence.

We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.

AI & Data - AI Strategy - Senior Manager - Oil & Gas Sector

As part of our growing AI & Data practice, we are seeking a highly experienced Senior Manager to lead enterprise AI strategy and quantitative modeling efforts for our clients in the Oil & Gas sector. This individual will bring deep industry expertise, along with a proven track record of designing and operationalizing responsible, scalable, and value-aligned AI solutions. You’ll lead high-impact client engagements focused on Generative AI, Agentic AI, MLOps, and AI governance frameworks — driving measurable outcomes in upstream, midstream, and downstream operations.

As a Senior Manager in AI Strategy, you will leverage proprietary, industry-aligned business models and innovative operating model designs to deliver impactful AI investments. You will be responsible for capability assessments, operating model design, product management, governance, and process design, ensuring that AI initiatives align with business strategies and stakeholder needs.

In this role, you will lead the delivery of complex AI strategies that enhance business effectiveness and efficiency. You will work closely with clients to envision how AI can transform their markets, products, and capabilities. This position offers the opportunity to engage with business and technology leaders, driving strategic programs that significantly impact their operations.

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• Lead engagement delivery, ensuring quality and risk management throughout the project lifecycle.
  
• Manage client relationships, focusing on revenue generation and the identification of new opportunities.
  
• Develop and manage resource plans and budgets for engagements, ensuring alignment with performance objectives.
  
• Define and implement enterprise-wide AI and quantitative modeling strategy tailored to oil & gas value chains (e.g., asset optimization, drilling, trading, predictive maintenance).
  
• Establish AI governance frameworks that ensure responsible AI adoption, ethical use of data, model risk management, and alignment with evolving regulations.
  
• Design and operationalize Agentic AI solutions to automate reasoning, planning, and decision‑making tasks in complex environments.
  
• Drive the prioritization of AI use cases based on business value, feasibility, and risk, ensuring ROI on AI initiatives.
  
• Lead multidisciplinary teams of data scientists, engineers, and consultants to deliver end‑to‑end AI platforms and solutions.
  
• Partner with senior business and IT leaders to identify strategic opportunities and shape AI‑enabled business transformation.
  
• Implement and scale ModelOps and MLOps practices, ensuring transparency, reproducibility, and monitoring of models in production.
  
• Lead AI solution architecture, including hybrid deployments on cloud (e.g. Microsoft Azure, Amazon AWS).
  
• Serve as a thought leader in emerging AI technologies, including Generative AI, foundation models, RAG and Agentic AI.
  
• Drive internal capability building and innovation in Responsible AI, agentic workflows, and energy sector‑specific solutions.
  

To excel in this role, you will need a blend of technical and interpersonal skills. Your ability to navigate complex challenges and deliver innovative solutions will be crucial.

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• Strong analytical and decision‑making skills to develop solutions to complex problems.
  
• Proven experience in managing client relationships and leading teams.
  
• Ability to communicate effectively and influence stakeholders at all levels.
  

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• Bachelor’s degree required; Master’s degree preferred with focus in Computer Science, Applied Math, or related field with prior consulting experience required.
  
• 10+ years of experience in technology consulting, digital transformation, or AI‑driven business solutions.
  
• 5+ years of leadership in AI/ML projects, including team management and executive stakeholder engagement.
  
• Typically, no less than 5 — 7 years of relevant experience.
  
• Strong expertise in AI Platforms and Tools.
  
• Proficiency in Data Architecture Design and Modelling.
  
• Experience in Digital Transformation and IT Effectiveness Assessment.
  
• Knowledge of Emerging Technologies and Technology Strategy, Vision, and Roadmap.
  
• Ability to build and manage relationships effectively.
  
• Strong exposure to oil & gas industry operations, value levers, and use case landscape.
  
• Proven success in developing AI strategy and governance models, including frameworks for Responsible AI, risk, and compliance.
  
• Hands‑on experience with Generative AI frameworks (e.g., OpenAI, Hugging Face, LangChain, RAG).
  
• Experience architecting and scaling MLOps platforms and data science workflows in cloud‑native environments.
  
• Proficiency in Python and tools like Pandas, PyTorch, Scikit‑learn, Spark, SQL.
  
• Experience with CI/CD, containerization (e.g., Docker, Kubernetes), and MLFlow or similar tools.
  
• Strong client‑facing skills with the ability to articulate technical topics to business executives.
  

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• Experience in managing change and leading teams.
  
• Strong negotiation and influencing skills.
  
• Familiarity with sector knowledge and commercial acumen.
  
• Prior experience leading AI initiatives in the energy or oil & gas sector, including exploration, refining, or energy trading.
  
• Familiarity with agentic AI concepts, cognitive architectures, and autonomous agents.
  
• Working knowledge of ESG data, climate risk modeling, and regulatory trends in energy.
  
• AI certifications (Microsoft, AWS, NVIDIA, Databricks, or equivalent).
  
• Exposure to agile delivery models and design thinking approaches.
  

We seek individuals who are not only skilled but also passionate about driving innovation and transformation through AI. Top performers are those who can think critically, solve complex problems, and communicate effectively with diverse stakeholders. If you are eager to make a significant impact and thrive in a collaborative environment, we want to hear from you!

At EY, we’ll develop you with future‑focused skills and equip you with world‑class experiences. We’ll empower you in a flexible environment, and fuel you and your extraordinary talents in a diverse and inclusive culture of globally connected teams. Learn more.

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  We offer a comprehensive compensation and benefits package where you’ll be rewarded based on your performance and recognized for the value you bring to the business. The base salary range for this job in all geographic locations in the US is $144,000 to $329,100. The base salary range for New York City Metro Area, Washington State and California (excluding Sacramento) is $172,800 to $374,000. Individual salaries within those ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options.

  
  
  
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  Join us in our team‑led and leader‑enabled hybrid model. Our expectation is for most people in external, client‑serving roles to work together in person 40‑60% of the time over the course of an engagement, project or year.

  
  
  
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  Under our flexible vacation policy, you’ll decide how much vacation time you need based on your own personal circumstances. You’ll also be granted time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well‑being.

  
  
  

Are you ready to shape your future with confidence? Apply today.

EY accepts applications for this position on an on‑going basis.

For those living in California, please click here for additional information.

EY focuses on high‑ethical standards and integrity among its employees and expects all candidates to demonstrate these qualities.

EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, genetic information, national origin, protected veteran status, disability status, or any other legally protected basis, including arrest and conviction records, in accordance with applicable law.

EY is committed to providing reasonable accommodation to qualified individuals with disabilities including veterans with disabilities. If you have a disability and either need assistance applying online or need to request an accommodation during any part of the application process, please call 1‑800‑EY‑HELP3, select Option 2 for candidate related inquiries, then select Option 1 for candidate queries and finally select Option 2 for candidates with an inquiry which will route you to EY’s Talent Shared Services Team (TSS) or email the TSS at .

Join the team leading the next evolution of virtual care.

At Teladoc Health, you are empowered to bring your true self to work while helping millions of people live their healthiest lives.

Here you will be part of a high-performance culture where colleagues embrace challenges, drive transformative solutions, and create opportunities for growth. Together, we're transforming how better health happens.

Summary of Position

Essential Duties and Responsibilities

• Work closely with business stakeholders toidentifyautomation opportunities.
• Lead the technical set up and integration ofconversational AI platform & agent development studiowithin the enterprise environment.- copilot agents preferred, deploying across enterprise not for personal use.
• Analyze business processes, data flows, and system architectures to support AI solution design.
• Support configuration and deployment of AI-powered agents,applications,and workflows.
• Design,build,and customize AI agents to automate workflows and improve productivity.
• Utilizedata platforms such asMicrosoft Fabric, Snowflake, Databricks, AWSfor data orchestration, governance, and compliance.
• Ensure seamless interoperabilityof agentsacrossMicrosoft and other enterprise applications asrequired.
• Evaluateand implement secure API integrationswith enterprise systems using APIsandconnectors to enable data exchange and workflow automation.
• Apply best practices for data security, identity management, and compliance with organizational and regulatory standards.
• Apply analytical judgment to assess feasibility, scalability, data readiness, and risks of AI use cases.
• Collaborate withcybersecurityand product teams to build robust AI solutions
• Test new AI agent enhancements, integrations, and fixes prior to release to ensure quality and expected behavior.
• Track and analyze performance metrics, including response quality, speed, reliability, andcost-effectivenessof AI agents and automated workflows.
• ContinuouslyoptimizeAI solutions based on performance data, user feedback, and evolving business needs.
• Document requirements, solution designs, architecture diagrams, and integration approaches in a clear and concise manner.
• Contribute to internal standards, reusable patterns, and best practices for AI agent and automation development.
• Support knowledge sharing and enablement across technical and business teams.

Qualifications Expected for Position

• Bachelor's degree in computer science, Information Systems, Engineering, Data Science, or a related fieldor equivalent combination of education and relevant professional experience.
• Advanced certifications or coursework in cloud platforms, data engineering, or AI/ML preferred.
• 3+years of experience in solution architecture, systems integration, automation engineering, or applied AI roles.
• 1+ year demonstrated ability to design, build, and deployAI-poweredagents, workflows, or conversational applications.
• Proven experience working directly with business stakeholders to translate operational needs into scalable technical solutions.
• Hands-on experience implementing enterprise automation or conversational AI solutions across multiple departments or use cases.
• Experienceoperatingin regulated orsecurity-consciousenvironments, supporting compliance and governance requirements.
• Strong experience designing and implementing enterprise system integrations using APIs, connectors, and automation frameworks.
• Experience working with modern data platforms (e.g.,Microsoft Fabric, Snowflake, Databricks, AWS) to support data orchestration, access control, and compliance.
• Solid understanding of identity management, access controls, and data security best practices.
• Ability to assess AI solution feasibility, including data readiness, scalability, performance, and cost considerations.
• Strong analytical andproblem-solvingskills with the ability to apply sound judgment to ambiguous or emerging AI use cases.
• Excellent written and verbal communication skills, with the ability to explain technical concepts to nontechnical audiences.

The base salary range for this position is$130,000 - $140,000. In addition to a base salary, this position is eligible for a performance bonus and benefits (subject to eligibility requirements) listed here: Teladoc Health Benefits 2026.Total compensation is based on several factors including, but not limited to, type of position, location, education level, work experience, and certifications.This information is applicable for all full-time positions.

We follow a Flexible Vacation Policy, intended for rest, relaxation, and personal time. All time off must be approved by your manager prior to use. You will also receive 80 hours of Paid Sick, Safe, and Caregiver Leave annually. This applies to full-time positions only. If you are applying for a part-time role, your recruiter can provide additional details.

As part of our hiring process, we verify identity and credentials, conduct interviews (live or video), and screen for fraud or misrepresentation. Applicants who falsify information will be disqualified.

Teladoc Health will not sponsor or transfer employment work visas for this position. Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future.

Why join Teladoc Health?

• Teladoc Health is transforming how better health happens. Learn how when you join us in pursuit of our impactful mission.

• Chart your career path with meaningful opportunities that empower you to grow, lead, and make a difference.

• Join a multi-faceted community that celebrates each colleague's unique perspective and is focused on continually improving, each and every day.

• Contribute to an innovative culture where fresh ideas are valued as we increase access to care in new ways.

• Enjoy an inclusive benefits program centered around you and your family, with tailored programs that address your unique needs.

• Explore candidate resources with tips and tricks from Teladoc Health recruiters and learn more about our company culture by exploring #TeamTeladocHealth on LinkedIn.

As an Equal Opportunity Employer, we never have and never will discriminate against any job candidate or employee due to age, race, religion, color, ethnicity, national origin, gender, gender identity/expression, sexual orientation, membership in an employee organization, medical condition, family history, genetic information, veteran status, marital status, parental status, or pregnancy). In our innovative and inclusive workplace, we prohibit discrimination and harassment of any kind.

Teladoc Health respects your privacy and is committed to maintaining the confidentiality and security of your personal information. In furtherance of your employment relationship with Teladoc Health, we collect personal information responsibly and in accordance with applicable data privacy laws, including but not limited to, the California Consumer Privacy Act (CCPA). Personal information is defined as: Any information or set of information relating to you, including (a) all information that identifies you or could reasonably be used to identify you, and (b) all information that any applicable law treats as personal information. Teladoc Health's Notice of Privacy Practices for U.S. Employees' Personal information is available at this link.

Role:

Join project teams across the U.S. as the on-site catalyst who turns AI ideas into working reality. Partnering with each project’s AI Champion (Project Manager or Superintendent), you’ll uncover pain points, redesign workflows, and deploy AI agents that cut down reporting, accelerate RFIs, simplify lookahead planning, progress updates, materials tracking, and more. When needed, you will develop user stories and coordinate development with the central AI Studio. You’ll help advance the vision of the “Construction Site of the Future,” showing how agentic AI will transform project operations.

Location: New Haven, Connecticut

Responsibilities:

• Opportunity hunting and workflow redesign – Lead Lean/Six Sigma discovery workshops; map value streams, assess process and data maturity, and log low-effort/high-impact AI use cases.
• Process and data maturity assessment – Evaluate each jobsite’s current workflows and underlying data; surface gaps that block AI adoption and develop phased improvement plans with Operations Excellence to establish the right process baseline before deploying agents.
• Assess the market solutions – Evaluate off-the-shelf and platform tools; launch pilots, measure impact, and scale wins.
• Rapid AI-agent builds – Convert user stories into production-ready agents in Copilot Studio / Power Apps/Automate, ChatGPT Enterprise, or code-first frameworks within days; wire them to Teams/SharePoint on the front end and Databricks Lakehouse or other sources on the back end.
• Enterprise-grade engineering & LLMOps – Build RAG pipelines backed by Delta tables, Unity Catalog, and Databricks Vector Search; automate infra with GitHub Actions / Posit; monitor latency, cost, adoption, and drift.
• Data integrations – Partner with Data Engineering to design and maintain ETL pipelines, API integrations, and event-driven connectors feeding RAG and agents.
• Cross-cloud orchestration – Blend OpenAI, Azure OpenAI, and AWS Bedrock behind secure custom connectors; package agents for seamless rollout.
• Change enablement – Train crews, gather feedback, iterate, and track adoption and ROI metrics; apply influence model principles to embed agents into daily routines and SOPs, and track behavior change KPIs.
• Stakeholder communication – Brief project leadership and clients on agent impact in clear business terms; contribute use cases and playbooks for “Construction Site of the Future.”
• Escalation & hand-off – Draft clear user stories, data specs, and acceptance criteria for any complex solution that requires the central AI Solution Engineers or Data Engineering / Data Science team to lean in.

Qualifications:

• 3+ years in AI engineering / full-stack data applications or data science, including 2+ years building production LLM/RAG solutions.
• Bachelor’s in CS, Engineering, Physics, or a related field; Master’s preferred.
• Prior hands-on work in construction or heavy process industries (manufacturing, oil & gas, chemicals) is a significant plus.
• Demonstrated process excellence background (Lean/Six Sigma Green Belt or equivalent) with experience diagnosing process and data gaps and supporting change management plans with Operations Excellence.
• Strong facilitation and communication skills.
• Hands-on expertise with Copilot Studio, Power Apps/Automate, custom connectors, and CoE Toolkit governance.
• Programming & data stack: Python, SQL, Databricks Lakehouse, vector stores.
• DevOps & IaC: GitHub Actions (or Azure DevOps) and Posit Workbench/Connect automation or comparable CI/CD tooling; strong Git/GitHub workflow discipline.
• Integration & ETL skills: Foundational understanding of ETL/ELT design, Airflow or Databricks Workflows, and REST/GraphQL API development; proven collaboration with Data Engineering on source-to-lake and lake-to-agent pipelines.
• Willing and able to travel and work on active jobsites.

Generative AI Engineer/Agentic Engineer

You bring AI to life - one agent at a time. At BWE, we rely on you to build smart, adaptive systems that act on behalf of our teams, streamlining workflows and amplifying impact. As an Agentic Engineer, you turn complex business tasks into intelligent, automated solutions that drive efficiency across the enterprise. Your work helps us scale AI with confidence, creativity, and control.

Responsibilities:

• Design, build, and optimize autonomous or semi-autonomous AI workflows (agentic systems) using Microsoft Copilot, Power Automate, Copilot Studio, and third-party AI platforms.
• Translate complex business tasks into orchestrated, multi-step AI workflows that can act with minimal user input while maintaining accuracy and compliance standards.
• Develop and iterate intelligent assistants, copilots, and AI agents to automate business processes across origination, closing, servicing, and corporate functions.
• Collaborate with Business Partners and business units to test, refine, and scale agentic tools that drive measurable efficiency improvements and user adoption.
• Lead implementation of BWE's Scale Agentic AI initiative by identifying high-impact automation opportunities and deploying production-ready AI agents.
• Partner with AIOps Engineer to ensure agentic systems integrate properly with monitoring, governance, and optimization frameworks.
• Stay ahead of emerging agentic design patterns, orchestration technologies, and best practices while bringing forward innovative solutions to business challenges.
• Create reusable agentic templates and workflow patterns that enable citizen developers to build AI-powered automation within governance frameworks.
• Implement security and compliance controls for agentic systems ensuring adherence to financial services regulations and data privacy requirements.
• Research and experiment with innovative agentic AI technologies and platforms to enhance BWE's automation capabilities.
• Provide training and support to business users adopting agentic tools and automation workflows.
• Document agentic system architectures, decision logic, and operational procedures for knowledge transfer and maintenance.

Near-Term Deliverables:

• Build and deploy at least 3-5 production agentic systems that demonstrate significant business impact and operational efficiency gains.
• Establish agentic AI development framework including design patterns, testing methodologies, and deployment standards.
• Create a comprehensive library of reusable agentic components and workflow templates that accelerate automation deployment across business functions.
• Partner with Business Partners to identify and prioritize high-impact opportunities for agentic AI implementation with detailed business case analysis.
• Develop agentic system monitoring and optimization practices ensuring reliable performance, accuracy, and cost efficiency.
• Research and recommend emerging agentic AI platforms and technologies for potential adoption with hands-on evaluation and implementation guidance.
• Create citizen developer enablement materials including agentic workflow templates, training resources, and best practice guidelines.
• Establish agentic AI governance practices including approval workflows, risk assessment, and compliance validation procedures.
• Complete advanced training in agentic AI, workflow orchestration, or emerging automation technologies relevant to enterprise applications.
• Contribute to BWE's competitive advantage by pioneering innovative agentic use cases and automation strategies.

Minimum Qualifications:

• 5+ years of experience building AI-driven workflows, intelligent automation, or low-code/no-code solutions in enterprise environments.
• Hands-on experience with Microsoft Power Platform (Power Automate, Power Apps), Microsoft Copilot Studio, and Large Language Model (LLM) integration.
• Strong grasp of prompt engineering, conversation design, logic flows, and business process optimization techniques.
• Experience with API integration, data transformation, and system connectivity for workflow automation.
• Knowledge of agentic AI concepts including multi-step reasoning, tool usage, and autonomous decision-making systems.
• Understanding of business process design, user experience principles, and change management for automation adoption.
• Bachelor's degree in Computer Science, Engineering, Business Technology, or related field, or equivalent work experience.
• Creative, fast-moving builder with prototyping mindset and deep understanding of user needs and business workflows.

Preferred Qualifications:

• Experience with advanced agentic AI platforms and orchestration tools beyond Microsoft ecosystem.
• Knowledge of machine learning, natural language processing, and conversational AI development.
• Familiarity with enterprise integration patterns, API management, and cloud-native application development.
• Experience in CRE, financial services, or regulated industries with complex compliance and audit requirements.
• Understanding of AI governance, responsible AI deployment, and risk management for autonomous systems.
• Previous experience leading automation initiatives or digital transformation projects.
• Knowledge of emerging technologies including multi-modal AI, autonomous agents, and AI orchestration platforms.

• Design and implement automated workflows and AI agents for supply chain tasks.
• Conduct iterative testing and user acceptance testing with supply chain teams.
• Configure workflow logic, decision trees, automation sequences, and integration points for AI functionality.
• Develop hybrid solutions integrating analytics dashboards with AI workflows for process automation.
• Document workflow configurations, prompt patterns, and decisions in detail for non-technical user maintenance.

• Expertise in prompt engineering and AI platform management
• Proficiency in no-code/low-code workflow automation tools
• Deep understanding of AI agent training, context windows, model limitations, and hallucination mitigation.
• Basic technical understanding (APIs, data structures, integrations)

Join the team leading the next evolution of virtual care.

At Teladoc Health, you are empowered to bring your true self to work while helping millions of people live their healthiest lives.

Here you will be part of a high-performance culture where colleagues embrace challenges, drive transformative solutions, and create opportunities for growth. Together, we're transforming how better health happens.

Summary of Position

The Principal AI Security Engineer is a senior technical leader on the AI Security team, responsible for designing, building, and operating security controls for generative AI and Machine Learning (ML) systems across their full lifecycle: data, training, deployment, and runtime.

This role is deeply hands-on: you will work directly with data science, MLOps, platform, devops and application teams to secure LLMs, RAG systems, AI agents, and AI-enabled products. You will also lead the intake and review process for AI use cases, helping the organization adopt AI safely and at scale in a highly regulated environment.

The ideal candidate combines:

* Strong security engineering and cloud architecture experience

* Deep, current familiarity with modern AI/LLM tooling and practices

* Familiar and can cover basic coding within the AI tooling space (python, others)

* The ability to communicate clearly with senior leadership and influence enterprise-wide strategy

Essential Duties and Responsibilities

Secure AI / ML platforms and workloads

* Lead security architecture and threat modeling for AI/ML systems, including LLMs, RAG pipelines, agents, and AI-powered applications.

* Design and implement security controls as code (services, libraries, infrastructure-as-code, policy-as-code) for AI/ML platforms and workloads.

* Lead and help setup the basic infrastructure needed to safely rollout AI - MCPs, LLMs, pipelines, Test harness for AI (ie: harmbench), intake automation.

* Partner with data science and MLOps teams to harden:

• Data ingestion and labeling
• Training and fine-tuning pipelines
• Model registries and deployment workflows
• Inference APIs, agents, and integrations

* Define and champion secure reference architectures and patterns for common AI use cases and focus on composable architecture.

AI use case intake & governance

* Design, implement, and continuously improve the intake, triage, and review process for AI/ML and generative AI use cases across the organization.

* Build and automate self-service workflows (e.g., request forms, risk questionnaires, routing, approvals) that balance speed of delivery with security, privacy, and compliance with a focus on risk scoring and scorecards.

* Define risk-based criteria for AI use case approval, including data sensitivity, model and vendor selection, integration patterns, and control requirements; this will involve in re-mapping the complete end to end lifecycle.

* Review proposed AI solutions from concept through deployment, providing clear, actionable guidance to product and engineering teams.

* Maintain visibility into the AI use case portfolio and risk posture, and provide regular reporting to leadership and governance bodies.

Monitoring, detection & assurance

* Establish and maintain monitoring and detection for AI-specific threats, such as:

• Prompt injection and jailbreak attempts
• Data exfiltration and sensitive data exposure
• Misuse or abuse of AI tools and agents
• Anomalous model or pipeline behavior

* Integrate AI/ML systems with existing logging, SIEM, and incident response processes.

* Lead or participate in AI-focused security assessments, red-teaming, and adversarial testing; drive remediation and verification.

Strategy, leadership & enablement

* Help define and evolve the organization's AI security strategy, standards, and roadmap in partnership with Security, Engineering, Data, Legal, Privacy, and Risk.

* Translate global privacy, data sovereignty, and regulatory requirements into practical technical controls for AI workloads across multiple cloud environments.

* Prepare and deliver executive-ready briefings and narratives on AI security risks, controls, and progress.

* Mentor other engineers and serve as THE internal subject matter expert on AI/ML security, generative AI, and LLM-based systems.

Qualifications Expected for Position

• 7+ years of experience in information security, security engineering, or related fields, including significant time building and securing production systems.
• 3+ years of hands-on experience with AI/ML technologies (such as LLMs, RAG, model training/fine-tuning, MLOps, or AI-powered products), including implementation of security controls or guardrails for these systems.
• Strong programming skills in one or more relevant languages (e.g., Python, TypeScript/JavaScript, Go, or similar), with a track record of contributing to production-grade tools, services, or libraries.
• Deep understanding of cloud security architecture and controls on at least one major cloud platform (AWS, Azure, or GCP), including identity, networking, secrets management, data protection, logging, and monitoring.
• Experience designing and implementing controls in a highly regulated environment; healthcare or financial services preferred.
• Demonstrated ability to lead complex technical initiatives across multiple teams, from problem definition through design, implementation, and adoption.
• Proven ability to communicate complex technical and risk topics clearly to both engineering teams and senior leadership.

Preferred Qualifications:

* Practical experience securing LLM- and genAI-based systems, such as:

• RAG architectures backed by internal data
• AI assistants, copilots, or agents integrated with enterprise tools
• Fine-tuned models and model hosting platforms

* Experience with AI IDE tools

• cursor, windsurfer, others
• Knows the security problems and has practical solutions that balances innovation with innovation.

* Familiarity with AI/ML frameworks and ecosystems (e.g., TensorFlow, PyTorch, Scikit-learn) and/or modern LLM development stacks and IDEs (e.g., API-based LLMs, self-hosted models, AI-enhanced coding tools).

* Experience with:

• Security for data pipelines, feature stores, and model registries
• Detection engineering or SIEM tuning for AI-related events
• Red-teaming or adversarial testing of AI systems

* Evidence of ongoing engagement with AI and security (such as side projects, open-source contributions, lab environments, publications, or conference talks).

* Familiarity with emerging AI security and safety standards and forward-looking industry guidance and horizon reports.

* Relevant certifications (e.g., cloud security, security engineering, or governance) are a plus.

* Strong analytical and problem-solving skills, with the ability to operate effectively in a fast-evolving technical and regulatory landscape.

* High level of integrity and ethical conduct.

This role is a fit if you:

* Regularly build, break, or secure AI/ML or LLM-based systems in your day-to-day work or personal projects.

* Are comfortable reading and writing code, experimenting with new AI tools, and wiring them into real systems.

* Enjoy turning ambiguous AI ideas and risks into concrete architectures, controls, and automation.

* Can move fluidly between deep technical discussions and concise, executive-level explanations.

This role is not a fit if you:

* Prefer to focus solely on policy, governance, or vendor assessments without hands-on technical work.

* Do not actively engage with current AI/LLM tooling, research, and emerging practices.

* "Describe a specific LLM or AI/ML system you have secured. What were the main risks and what controls did you implement?"

* "What AI tools, libraries, or environments do you actively use or experiment with today (work or personal), and for what?"

* "What do you see as the most important AI security or safety developments on the horizon over the next few years, and why?"

The base salary range for this position is$180,000 - $190,000. In addition to a base salary, this position is eligible for a performance bonus and benefits (subject to eligibility requirements) listed here: Teladoc Health Benefits 2026.Total compensation is based on several factors including, but not limited to, type of position, location, education level, work experience, and certifications.This information is applicable for all full-time positions.

We follow a Flexible Vacation Policy, intended for rest, relaxation, and personal time. All time off must be approved by your manager prior to use. You will also receive 80 hours of Paid Sick, Safe, and Caregiver Leave annually. This applies to full-time positions only. If you are applying for a part-time role, your recruiter can provide additional details.

As part of our hiring process, we verify identity and credentials, conduct interviews (live or video), and screen for fraud or misrepresentation. Applicants who falsify information will be disqualified.

Teladoc Health will not sponsor or transfer employment work visas for this position. Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future.

Why join Teladoc Health?

• Teladoc Health is transforming how better health happens. Learn how when you join us in pursuit of our impactful mission.

• Chart your career path with meaningful opportunities that empower you to grow, lead, and make a difference.

• Join a multi-faceted community that celebrates each colleague's unique perspective and is focused on continually improving, each and every day.

• Contribute to an innovative culture where fresh ideas are valued as we increase access to care in new ways.

• Enjoy an inclusive benefits program centered around you and your family, with tailored programs that address your unique needs.

• Explore candidate resources with tips and tricks from Teladoc Health recruiters and learn more about our company culture by exploring #TeamTeladocHealth on LinkedIn.

As an Equal Opportunity Employer, we never have and never will discriminate against any job candidate or employee due to age, race, religion, color, ethnicity, national origin, gender, gender identity/expression, sexual orientation, membership in an employee organization, medical condition, family history, genetic information, veteran status, marital status, parental status, or pregnancy). In our innovative and inclusive workplace, we prohibit discrimination and harassment of any kind.

Teladoc Health respects your privacy and is committed to maintaining the confidentiality and security of your personal information. In furtherance of your employment relationship with Teladoc Health, we collect personal information responsibly and in accordance with applicable data privacy laws, including but not limited to, the California Consumer Privacy Act (CCPA). Personal information is defined as: Any information or set of information relating to you, including (a) all information that identifies you or could reasonably be used to identify you, and (b) all information that any applicable law treats as personal information. Teladoc Health's Notice of Privacy Practices for U.S. Employees' Personal information is available at this link.

By clicking the "Apply" button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda's Privacy Notice and Terms of Use. I further attest that all information I submit in my employment application is true to the best of my knowledge.

Job Description

Role Summary

Lead the strategy, platform build-out, and adoption of AI/ML across Research for global digital transformation effort, making AI agents, models, and tools a daily, accessible part of wet‐lab and dry‐lab scientists' workflows. Translate AF priorities into a practical, compliant AI services layer—data foundations, MLOps, agentic assistants, model governance, and change enablement—that shortens time from experiment to insight and elevates decision quality across discovery programs.

Objectives / Purpose

• Define and execute a multi‐year AI/ML roadmap aligned to Research use cases and KPIs.
• Establish an AI‐ready data foundation (FAIR-by-design) and scientist‐facing AI tools embedded in ELN/LIMS/instrument workflows.
• Institutionalize Responsible AI & GxP-aware governance for production models.
• Drive adoption through super-user networks, training, and change management to achieve measurable value and ROI.

Scope / Impact

Global Research scope with cross‐site collaboration (US/EU/JP). Direct impact on data-to-decision latency, assay/analysis reproducibility, and portfolio productivity. Partner with operations, Computational Sciences & Data Strategy, IT, function leads, and platform teams to deliver outcomes at scale.

Accountabilities

Strategy & Roadmap

• Own Research's AI/ML strategy and sequencing (MVP → scale) across wet‐lab dry‐lab integration and self‐service tools.
• Align priorities with Research's KPIs and portfolio goals; establish and monitor achievement of success criteria and milestones.

Platform, Data & Integration

• Guide the development of AI‐ready data foundations (provenance, metadata/ontologies, harmonization) across ELN/LIMS, instruments, imaging, and omics.
• Integrate platforms (e.g., ELN, SDMS & AI Cloud) to liberate, contextualize, and operationalize lab data for AI/ML.
• Stand up modern MLOps (CI/CD, registries, experiment tracking, monitoring) and secure service/APIs embedded in workflows.

Agentic AI & Productization

• Design self-service and user-friendly processes for deployment of AI agents for scientists (literature triage, protocol assist, data QC, analysis pipelines, code helpers).
• Guide engineering efforts to deliver production models (e.g., sequence/structure prediction, assay QC, outlier detection, multimodal analytics).

Adoption & Change Enablement

• Lead adoption via super‐user networks, training, and communications; co‐own readiness plans with NCSP.
• Work with Change Management leads to publish playbooks and guardrails enabling self‐service AI workflows for scientists.

Governance, Risk & Compliance

• Define and Implement Responsible AI and risk‐based governance (ALCOA+, validation mindset, audit trails, XAI, privacy/PII controls).

Impact & Reporting

• Own measurable impact (adoption, latency, reproducibility, ROI) and provide transparent reporting to R&D leadership and key stakeholders.

Qualifications

Required

PhD degree in a scientific discipline with 10+ years experience , or

MS with 16+ years experience, or BS with 18+ years experience (preferably in Advanced degree in Computer Science, AI/ML, Computational Biology/Chemistry, Bioinformatics, or related; or equivalent industry experience.)

Proven MLOps platform build and delivery of scientist‐facing AI tools embedded in ELN/LIMS/instrument workflows.

Expertise in FAIR data, scientific data models/ontologies, and integration across wet‐lab instruments, imaging, and omics.

Experience with Responsible AI and GxP‐adjacent validation/governance in pharma/biotech R&D.

Strong stakeholder management; ability to translate complex science/data into usable AI for end users.

Preferred

• Experience working in wet-labs and knowledge of Research and Development workflows and processes in either the biologics and/or small molecule fields
• Agentic AI systems and LLMs for scientific contexts; multimodal ML (text/images/sequences/numerical).
• Knowledge of Research/Pharma Sci common data models and cloud analytics/HPC integrations.

Takeda Compensation and Benefits Summary

We understand compensation is an important factor as you consider the next step in your career. We are committed to equitable pay for all employees, and we strive to be more transparent with our pay practices.

For Location:

U.S. Base Salary Range:

U.S. based employees may be eligible for short-term and/ or long-term incentives. U.S. based employees may be eligible to participate in medical, dental, vision insurance, a 401(k) plan and company match, short-term and long-term disability coverage, basic life insurance, a tuition reimbursement program, paid volunteer time off, company holidays, and well-being benefits, among others. U.S. based employees are also eligible to receive, per calendar year, up to 80 hours of sick time, and new hires are eligible to accrue up to 120 hours of paid vacation.

EEO Statement

Takeda is proud in its commitment to creating a diverse workforce and providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, parental status, national origin, age, disability, citizenship status, genetic information or characteristics, marital status, status as a Vietnam era veteran, special disabled veteran, or other protected veteran in accordance with applicable federal, state and local laws, and any other characteristic protected by law.

Locations

Worker Type

Worker Sub-Type

Time Type

Job Exempt

By clicking the "Apply" button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda's Privacy Notice and Terms of Use. I further attest that all information I submit in my employment application is true to the best of my knowledge.

Job Description

At Takeda, we are a forward-looking, world-class R&D organization that unlocks innovation and delivers transformative therapies to patients. By focusing R&D efforts on three therapeutic areas and other targeted investments, we push the boundaries of what is possible to bring life-changing therapies to patients worldwide.

The AI/ML organization at Takeda is building a team to transform how medicines are discovered. Our goal is to apply AI and machine learning across the entire drug discovery process, not just isolated steps, but as an integrated approach from target identification through development. This requires discernment: knowing which models and methods fit each problem, and the creativity to adapt when they don't. We work with foundational models, generative approaches, and autonomous systems, but the tools only matter when paired with people who understand the science deeply enough to use them well. Our team brings together computational scientists, biologists, engineers, and drug hunters. If you want to contribute your expertise to hard problems alongside colleagues with different perspectives and help shape how AI delivers real impact in drug discovery, we'd like to hear from you.

Position Overview

We are seeking Senior Scientists to develop agentic AI systems that transform how drug discovery research is conducted. As part of the AI/ML Foundation team, you will build autonomous AI agents capable of reasoning, planning, and executing complex scientific workflows—from literature synthesis and target identification to experimental design and data analysis. This role requires a unique combination of expertise in large language models, agentic frameworks, and understanding of drug discovery processes. You will translate standard research workflows into agentic frameworks, develop new agent skills, and deploy systems that augment scientist productivity across Computational Sciences and Global Research.

Accountabilities:

• Develop agentic AI systems for drug discovery applications including target-disease association, automated literature search and synthesis, hypothesis generation, and intelligent design of experiments.
• Translate standard research workflows into agentic frameworks—decomposing complex scientific processes into autonomous agent tasks that can reason, plan, execute tools, and iterate based on results.
• Design and implement new agent skills (tools, functions, APIs) that extend agentic capabilities to specialized scientific domains including molecular design, property prediction, assay planning, and data analysis.
• Build agentic systems that integrate with foundation models and external knowledge sources for autonomous hypothesis generation, evidence retrieval, and scientific reasoning.
• Develop retrieval-augmented generation (RAG) pipelines connecting agents to internal and external scientific literature, databases, and experimental results.
• Partner with research scientists to understand workflow needs, validate agent outputs, and iterate on system design to ensure scientific rigor and utility.
• Stay current with advances in agentic AI, LLM applications, and scientific automation; contribute to internal knowledge sharing and external publications.

Educational & Requirements:

• PhD in Computer Science, Computational Biology, Bioinformatics, or related field with 2+ years relevant experience, OR MS with 6+ years relevant experience.
• Strong experience with large language models (GPT, Claude, Llama) and their application to complex reasoning tasks.
• Proficiency in Python and experience with agentic AI frameworks (LangChain, AutoGen, CrewAI, or similar).
• Experience building RAG systems including vector databases, embedding models, and retrieval pipelines.
• Understanding of drug discovery processes and scientific research workflows.
• Strong problem-solving skills and ability to translate complex scientific processes into computational workflows.

Preferred:

• Experience in pharmaceutical or biotech R&D environments.
• Background in biology, chemistry, or disease biology.
• Experience with reinforcement learning or planning algorithms for agent decision-making.
• Familiarity with scientific databases (PubMed, UniProt, ChEMBL) and APIs.
• Experience deploying AI systems in production environments.
• Track record of publications or presentations on LLM ap

Additional Competencies Common in Strong Candidates

• Ability to lead cross-functional initiatives and mentor junior scientists.
• Experience in translating computational insights into experimental strategies.
• Strong publication record or demonstrated thought leadership in AI for biology and molecular design.
• Comfort working in fast-paced, innovation-driven environments with evolving priorities.

ADDITIONAL INFORMATION

• The position will be based in Cambridge, MA

Takeda Compensation and Benefits Summary

We understand compensation is an important factor as you consider the next step in your career. We are committed to equitable pay for all employees, and we strive to be more transparent with our pay practices.

For Location:

U.S. Base Salary Range:

U.S. based employees may be eligible for short-term and/ or long-term incentives. U.S. based employees may be eligible to participate in medical, dental, vision insurance, a 401(k) plan and company match, short-term and long-term disability coverage, basic life insurance, a tuition reimbursement program, paid volunteer time off, company holidays, and well-being benefits, among others. U.S. based employees are also eligible to receive, per calendar year, up to 80 hours of sick time, and new hires are eligible to accrue up to 120 hours of paid vacation.

EEO Statement

Takeda is proud in its commitment to creating a diverse workforce and providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, parental status, national origin, age, disability, citizenship status, genetic information or characteristics, marital status, status as a Vietnam era veteran, special disabled veteran, or other protected veteran in accordance with applicable federal, state and local laws, and any other characteristic protected by law.

Locations

Worker Type

Worker Sub-Type

Time Type

Job Exempt

Onsite AI Engineer - Construction Industry Focus

New Haven, CT - Onsite 5 days per week

• Initial Assignment: Fully onsite 5 days per week at a construction site in Ft. Myers (FL) or New Haven (CT) for 1 year
• Post-Assignment: Relocation to one of the corporate offices for hybrid employment: Boston, MA (preferred), New York City (NY), New Haven (CT), Herndon (VA), West Palm Beach (FL), or Estero (FL)

Role Summary

As the on-site catalyst who turns AI ideas into working reality. Partnering with each project’s AI Champion (Project Manager or Superintendent), you’ll uncover pain points, redesign workflows, and deploy AI agents that cut down reporting, accelerate RFIs, simplify lookahead planning, progress updates, materials tracking, and more. When needed, you will develop user stories and coordinate development with the central AI Studio. You’ll help advance the vision of the “Construction Site of the Future,” showing how agentic AI will transform project operations.

Responsibilities

• Workflow discovery and redesign: Lead Lean/Six Sigma workshops; map value streams; log high-impact AI agent opportunities that improve field efficiency.
• AI agent development: Build and deploy multiple production-ready AI agents using Copilot Studio, Power Apps/Automate, ChatGPT Enterprise, or code-first frameworks. Integrate agents into Teams/SharePoint on the front end and Databricks Lakehouse or other enterprise data sources on the back end.
• RAG pipelines and LLMOps: Design and operate retrieval-augmented generation (RAG) pipelines with Databricks Delta Tables, Unity Catalog, and Vector Search (or Spark/Hadoop equivalents). Monitor cost, latency, adoption, and model drift.
• Cross-cloud orchestration: Blend OpenAI, Azure OpenAI, and AWS Bedrock services through secure custom connectors to maximize flexibility and adoption.
• Data integration: Partner with Data Engineering to deliver ETL/ELT pipelines, API integrations, and event-driven connectors that feed RAG pipelines and AI agents.
• Change management and adoption: Train field teams, gather feedback, iterate quickly, and embed agents into SOPs. Track usage and ROI with adoption metrics and behavior-change KPIs.
• Stakeholder communication: Translate technical results into business value for leadership and clients. Contribute use cases and playbooks for the “Construction Site of the Future.”
• Compliance and hand-offs: Ensure all AI solutions meet the company’s data governance and security standards. Draft clear user stories and specs for escalation to central AI/Data Engineering teams when necessary.

Qualifications

• 4+ years in AI engineering, data science, or ML-focused software engineering.
• Proven experience building multiple AI agents in production environments.
• 2+ years of hands-on experience with LLMs, RAG pipelines, and LLMOps practices.
• Must have strong traditional software engineering background in Python

Bonus Points

• Experience in construction, manufacturing, or other process-heavy industries.
• Advanced degree in a technical field.

Propy is revolutionizing the real estate industry by building the world's first AI-powered Title and Escrow platform onchain. We have processed over $5B in transactions, and we are on a mission to make closing on a home as easy as buying a stock.

We combine blockchain for security with advanced AI to automate the heavy lifting of closing documents. We aren't just "using" AI; we are building the infrastructure that allows AI agents to securely manage escrow, eliminate fraud, and run 24/7.

We are looking for a pragmatic Applied AI Engineer to join our engineering team.

The role is not about training models and does not involve academic Machine Learning research. It is about building the rails that make AI usable in a high-stakes financial environment. You will bridge the gap between our robust C#/.NET architecture and the probabilistic world of LLMs.

Title and Escrow is a document-heavy industry with zero room for error. Your mission is to use AI to clean up the messiness of real-world real estate data.

You will solve problems like:

• Structured Data Extraction: Converting messy, unstructured data (like emails, PDFs, documents)  from various sources into strictly validated JSON schemas with as close to 100% accuracy as possible.
• Escrow Automation: Designing workflows that reduce human intervention by 50% by intelligently routing tasks based on AI analysis.
• Fraud Detection: Implementing deterministic logic checks on bank and financial documents to detect fraud patterns before they happen.

• Engineer the Integration: Writing production-grade code that interacts with external AI APIs
• "Prompt Engineering" as Code: You won't just write prompts; you will version, test, and optimize them. You will define strict schemas to ensure the AI speaks the language of our internal tools.
• Orchestrate & Validate: Help in building the logic that parses AI responses, validates them against our database (MongoDB), and flags inconsistencies before they reach the user.
• Full-Stack Implementation: Work to visualize AI-aided services and data for user review and approval.
• Collaborate: Work closely with the other senior engineers and product owners to translate complex "Title & Escrow" schemas into technical constraints that an AI can understand.

• Developer DNA: You are a software engineer first. You have strong experience in Python (C# / .NET is an advantage) and understand programming in depth. 
• Applied AI Experience: You have integrated LLMs into applications via API. Have experience with not only models but also AI frameworks. Experience with workflows, AI agent building and orchestration. You understand context windows, token limits, temperature, and guardrails.
• Data Handling: Experience with handling complex data structures.
• The "Glue" Mindset: You enjoy writing the code that connects different services ( like the AWS, AI APIs, and Database) to make a seamless features.
• Collaborative Autonomy: You will own the AI domain, but you won't be on an island. You will be embedded in a senior engineering team that supports you with architecture, code reviews, and best practices.

• Experience with AWS infrastructure.
• Familiarity with the US Real Estate, Title, or Escrow process.

• Working in a transparent environment which focuses on solving problems and getting things done.
• The opportunity to work with very smart and driven people.
• The ability to grow your talents and career in a high-growth sector.
• A remuneration package that is based on the candidate's motivation, skills, and experience.

Please submit your resume to this job ad along with a portfolio of your AI-related experience, GitHub account and anything else you find applicable. 

Position Title: Applied AI Systems Engineer

Location: Orange County, California (Hybrid)

Reports To: Head of Operations

Position Summary

This role is responsible for architecting, building, and deploying a production-grade AI operating system that automates core workflows across leasing, property management, accounting, construction coordination, and asset management.

The engineer will design and implement AI agents, document intelligence systems, and workflow automation pipelines that reduce manual processing, improve accuracy, and increase operational scalability across a commercial real estate portfolio.

This position requires strong systems thinking, rigorous technical execution, and the ability to translate complex operational processes into reliable automation.

Core Objectives

• Build an internal AI platform that automates high-volume operational workflows
• Reduce manual processing time and administrative overhead
• Improve accuracy, speed, and decision visibility across departments
• Establish scalable systems that support portfolio growth without proportional staffing increases

Primary Responsibilities

• AI Platform Architecture & Development
• Design and deploy AI agents to automate operational and administrative workflows
• Build LLM-powered systems for document review, data extraction, and decision support
• Develop retrieval-based systems leveraging leases, financial data, contracts, and SOPs
• Implement evaluation, monitoring, and continuous improvement frameworks

Lease & Document Intelligence Automation

• Build tools to extract key lease terms, obligations, and risk clauses
• Automates lease abstraction and document comparison workflows
• Develop compliance and deadline tracking systems
• Enable searchable knowledge retrieval across lease and legal documents

Leasing & Asset Management Automation

• Automate LOI comparison and deal workflow summaries
• Build dashboards summarizing tenant performance, lease milestones, and risk exposure
• Support market intelligence and tenant prospecting research
• Develop underwriting support and reporting tools

Property Management & Financial Workflow Automation

• Automate CAM reconciliation data processing and variance detection
• Streamline tenant reporting and communication workflows
• Track vendor contracts, compliance deadlines, and service obligations
• Extract and structure financial data from operational documents

Data Infrastructure & Knowledge Systems

• Structure internal documents and data for AI retrieval and automation
• Build document ingestion, indexing, and retrieval pipelines
• Implement vector search and knowledge retrieval systems
• Maintain data integrity, access control, and auditability

Systems Integration & Deployment

• Integrate AI tools with property management, accounting, CRM, and document platforms
• Deploy systems within secure cloud environments
• Implement logging, monitoring, performance, and cost controls
• Ensure reliability and scalability of deployed systems

Collaboration & Implementation

• Translate operational workflows into technical automation solutions
• Work directly with leadership to prioritize automation opportunities
• Train teams and implement adoption workflows
• Establish standards for responsible and secure AI usage

Required Qualifications

• Bachelor’s or advanced degree in Computer Science, Engineering, Mathematics, Statistics, or related quantitative discipline
• Demonstrated success in a rigorous academic or research environment
• 3–7+ years building production software, automation systems, or applied AI solutions
• Strong Python development and API integration experience
• Experience working with structured and unstructured data
• Experience deploying systems in cloud environments
• Strong understanding of system architecture and data pipelines
• Exceptional analytical and problem-solving ability

Preferred Qualifications

• Experience building document intelligence or contract analysis systems
• Experience with retrieval systems and vector databases
• Experience automating financial or operational workflows
• Experience integrating AI into business operations environments
• Experience in real estate, finance, logistics, or operations-heavy industries
• Evidence of research, technical publications, competitive programming, or open-source contributions

Technical Environment (Representative)

• Python and API-based architectures
• LLM platforms and agent orchestration frameworks
• Cloud infrastructure (AWS, Azure, or GCP)
• SQL and vector databases
• Workflow orchestration and automation tools
• Version control, logging, and monitoring systems

Success Metrics

• Performance in this role will be evaluated by:
• Reduction in manual administrative workload
• Automation coverage across operational workflows
• Accuracy and reliability of AI-driven outputs
• Adoption and usage across departments
• Operational efficiency gains and cost reductions

Work Environment

• Hybrid work model with in-person collaboration in Orange County
• Direct collaboration with executive leadership and operational teams
• High autonomy in system architecture and implementation decisions

AI Business Analyst

Department: IT

Reporting To: SVP, Technology & Digital Innovation

Location (On-Site): New York, NY - Fashion District

About G-III Apparel Group, Ltd. | Apparel Group is a global leader in design, sourcing, manufacturing, distribution, and marketing. We bring excitement and confidence to customers through the fashion we create. With more than 30 owned and licensed brands, including some of the most recognized names in global fashion, our success is driven by entrepreneurial thinking, operational excellence, and strong industry partnerships.

Position Summary

The AI Business Analyst will play a critical role in advancing G-III’s enterprise AI strategy by evaluating emerging AI technologies, identifying high-value business use cases, managing vendor assessments, and driving adoption across brands and functions. This position bridges technology and business operations—helping teams understand, pilot, scale, and operationalize AI capabilities that improve productivity, creativity, and decision-making.

In addition to third-party AI tools, this role will support the change management and adoption of internally developed AI solutions and models, ensuring new capabilities are introduced in a structured, well-communicated, and measurable manner.

This role will also be responsible for developing training materials, documenting best practices, creating video tutorials, and maintaining the AI Center of Excellence (AI CoE) SharePoint site as the central hub for AI knowledge, tools, governance standards, and success stories.

Key Responsibilities

AI Discovery & Assessment

• Evaluate AI tools, platforms, and vendors for business fit, ROI potential, data security, and scalability.
• Partner with functional leaders to identify, prioritize, and document AI use cases across merchandising, marketing, ecommerce, customer care, design, and operations.
• Develop value models and pilot plans to quantify business impact and organizational readiness for scale.

Pilot Execution & Measurement

• Design and oversee proof-of-value (POV) pilots with defined success criteria, control groups, and KPIs.
• Track adoption, productivity gains, time savings, and qualitative feedback to determine scalability and readiness.
• Present business cases, pilot outcomes, and recommendations to leadership and the AI CoE Steering Committee.

Change Management & Adoption

• Lead structured change management efforts for third-party AI tools and internally developed AI models and capabilities.
• Develop rollout plans including stakeholder mapping, communication strategies, training programs, and post-launch reinforcement.
• Partner cross-functionally with Business, IT, Legal, and HR teams to manage organizational readiness, role impacts, and process changes introduced by AI.
• Capture end-user feedback and operational learnings to inform iterative enhancements and future AI releases.

Training & Enablement

• Create training materials including written documentation, SOPs, and short-form instructional videos using tools such as Synthesia, Guidde, or similar platforms.
• Deliver live and recorded training sessions to cross-functional teams and AI Champion groups.
• Maintain and continuously enhance the AI CoE SharePoint site by organizing learning content, use cases, FAQs, governance documentation, and vendor updates.

Governance & Best Practices

• Ensure responsible AI adoption aligned with legal, privacy, data security, and brand standards.
• Document AI usage guidelines, data handling policies, governance frameworks, and onboarding checklists.
• Serve as an internal ambassador for AI literacy, ethical adoption, and best practices across the organization.

Reporting & Continuous Improvement

• Establish and track performance metrics including adoption rates, productivity gains, cost savings, and quality improvements.
• Publish dashboards and executive-ready performance summaries for leadership review.
• Stay current on enterprise AI developments, emerging tools, and internal platform enhancements to inform roadmap recommendations.

Qualifications

Required

• 4–7 years of professional experience in business analysis, enablement, product operations, or digital transformation, preferably within retail, apparel, or ecommerce.
• Hands-on experience using AI tools including ChatGPT Enterprise, Microsoft 365 Copilot, Synthesia, Guidde, or similar platforms.
• Strong analytical skills including ROI modeling, time-savings estimation, and pilot performance measurement.
• Experience creating training content (written and video) and managing enterprise enablement platforms such as SharePoint.
• Excellent written and verbal communication skills with the ability to translate technical capabilities into clear business value.

Preferred

• Familiarity with Shopify ecommerce platforms and PIM/DAM systems such as Salsify or Aprimo.
• Experience with enterprise collaboration tools including Microsoft Teams, Power BI, and Microsoft 365.
• Basic understanding of prompt engineering, generative AI limitations, and responsible AI frameworks.
• Experience working within multi-brand or multi-region organizations.
• Certifications in Microsoft 365 Copilot Service Adoption, Prosci Change Management, or AI Product Enablement preferred.

Core Competencies

• Business Impact Orientation: Drives measurable outcomes and quantifies value creation.
• Change Leadership: Leads structured adoption efforts across brands and departments.
• Structured Thinking: Translates complex technology into actionable business processes.
• Collaboration: Builds strong relationships with internal stakeholders and external partners.
• Communication Excellence: Produces clear, engaging materials for technical and non-technical audiences.
• Adaptability: Remains current with emerging AI technologies and evolving enterprise priorities.

What We Offer

• Competitive base salary and performance-based incentives
• Comprehensive medical, dental, and vision benefits
• 401(k) with company match
• Paid time off, holidays, and company-sponsored wellness benefits
• Employee discounts across G-III brands
• A collaborative, entrepreneurial work environment with career growth opportunities

Compensation

Salary Range: $105,000 – $125,000 base (commensurate with experience)

Please note that the foregoing compensation information is a good-faith assessment associated with this position only and is provided pursuant to the New York City Salary Transparency Law.

G-III’s owned brands include DKNY, Karl Lagerfeld Paris, Donna Karan, Vilebrequin, Sonia Rykiel, G.H. Bass, Bass Outdoor, Andrew Marc, Eliza J., G-III Sports and more. G-III holds licenses for Calvin Klein, Tommy Hilfiger, Cole Haan, Dockers, Guess?, Kenneth Cole, Levi’s, Vince Camuto, Margaritaville, and others. The company also operates retail stores for DKNY, Karl Lagerfeld Paris, and Donna Karan.