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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 .

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. 

Senior Applied AI Engineer (End-to-End ML)

Location: Palo Alto, CA (Hybrid )

Role Type: Full-Time / Permanent

Summary

Our client, a pioneering HealthTech AI firm in the Bay Area, is seeking a high-calibre Applied AI Engineer to bridge the gap between advanced Machine Learning and robust Software Engineering. This is an end-to-end ownership role: you will be responsible for designing the logic, building the architecture, and deploying the final services.

Core Responsibilities

• Architect AI Workflows: Design and implement sophisticated agentic workflows and automation sequences that power clinical decision-making.
• System Design & Integration: Build the backend infrastructure, scalable REST APIs, and data services required to support high-concurrency AI applications.
• Rapid Deployment: Maintain a high-velocity shipping cycle, moving from prototype to production-grade implementation in days.
• Model Orchestration: Select, fine-tune, and evaluate the performance of various LLMs (including OpenAI, Anthropic, and open-source models) for specific healthcare tasks.
• Full-Stack ML: Own the pipeline from data ingestion and time-series forecasting to real-time classification and model monitoring.

Technical Profile

• Computer Science Mastery: Expert knowledge of algorithms, data structures, and distributed systems.
• Software-Heavy Background: Professional-grade Python skills. You should be comfortable with software design patterns, testing, and CI/CD.
• Machine Learning Fundamentals: * Deep understanding of Core ML topics: classification, regression, and clustering.
• Specific experience in Time Series Forecasting and temporal data analysis.
• Proficiency in Generative AI: RAG architectures, prompt optimization, and agent frameworks.
• Infrastructure: Experience deploying services to cloud environments (GCP preferred) and a solid grasp of MLOps and pipeline automation.
• Education: BS in Computer Science or related field + 4 years of experience, or an MS + 2 years of experience.

Cultural Fit

• Startup Agility: You possess the "scrappiness" to solve problems with limited resources but the rigor to ensure those solutions are enterprise-grade.
• The "Generalist" Mindset: You enjoy working across the entire stack and are not afraid to dive into data engineering or infrastructure when needed.
• Mission-Oriented: You are motivated by the prospect of using AI to significantly improve patient outcomes and healthcare efficiency.

What’s Offered

Our client provides a highly competitive package, including a strong base salary, meaningful equity, and comprehensive premium healthcare benefits. You will join a world-class team of engineers in a collaborative, hybrid environment.

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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.
  

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

We are seeking a Senior Scientist to lead the design and implementation of AI orchestration systems within the AI/ML Foundation team. This role combines expertise in agentic AI systems, data engineering, and software architecture to build the infrastructure that enables seamless coordination of AI capabilities across Computational Sciences and Global Research. You will be responsible for creating intelligent orchestration layers that connect diverse AI models, data pipelines, and computational resources to accelerate drug discovery across all therapeutic modalities. The ideal candidate brings strong engineering fundamentals with experience in distributed systems and a passion for building scalable AI platforms.

Accountabilities:

• Design and implement AI orchestration frameworks that integrate agentic systems, data pipelines, and model serving infrastructure to enable coordinated multi-model workflows.
• Build scalable orchestration layers connecting predictive models, generative models, and foundation models with experimental data sources for end-to-end workflow automation.
• Develop data engineering solutions including data ingestion pipelines, transformation workflows, feature stores, and model serving infrastructure supporting discovery across modalities.
• Create intelligent orchestration systems that coordinate agentic AI components for autonomous task decomposition, tool selection, and execution across scientific domains.
• Establish monitoring, observability, and governance frameworks ensuring reliability, reproducibility, and transparent decision-making across AI systems.
• Partner with computational scientists, data engineers, and research teams to ensure orchestration infrastructure meets the needs of diverse discovery workflows.
• Stay current with advances in agentic AI, workflow orchestration, and distributed systems; evaluate and integrate emerging technologies.

Education & Requirements:

• PhD in Computer Science, Data Engineering, Computational Science, or related field with 2+ years relevant experience, OR MS with 6+ years relevant experience.
• Strong software engineering skills with proficiency in Python and experience with distributed systems and cloud infrastructure (AWS, GCP).
• Experience with workflow orchestration frameworks (Airflow, Prefect, Dagster, or similar) and data pipeline development.
• Familiarity with agentic AI frameworks (LangChain, AutoGen, or similar) and LLM integration patterns.
• Experience with containerization (Docker, Kubernetes) and microservices architecture.
• Strong problem-solving skills and ability to work across teams in a fast-paced R&D environment.

Preferred:

• Experience building AI/ML platforms or infrastructure in pharmaceutical or life sciences settings.
• Familiarity with scientific computing workflows and computational chemistry/biology tools.
• Experience with model serving frameworks (TorchServe, Triton, BentoML) and feature stores.
• Knowledge of monitoring and observability tools (Prometheus, Grafana, MLflow).
• Experience with event-driven architectures

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

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Time Type

Job Exempt

With data being the fuel that drives our future - our strategies, policies, and business successes around data will define our future growth prospects. Unlocking the value available through the innovative use of data on behalf of consumers, businesses, and communities is key to our future. With our ongoing commitment to Visa’s Data Values and the responsible use of data, we at Visa have a bold vision to continue to grow and accelerate our data-

The AI Products & Analytics team under the Global Data Office is creating the next generation of scalable and responsible AI, ML and Data solutions and products to solve client and consumer problems. We are a cross‑functional team of data scientists, product/program managers, data engineers and ML Engineers focused on generating value for the payment ecosystem. We are dreaming of the next generation of AI features and products, Agentic AI solutions and high‑quality analytics and data science support for our internal partner teams.

This position is in the AI Practices & COE sub‑team under the AI Products & Analytics team, focused on AI Transformation of the Global Data Office. The AI Transformation program aims to accelerate operational efficiency and foster innovation through targeted automation. By deploying scalable AI solutions to existing time‑consuming workflows with high potential for AI disruption, this will ensure measurable, sustainable benefits across the Global Data Office.

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• Design and implement agentic AI workflows to automate multi‑step tasks and drive business impact.
  
• Integrate predictive, generative, and prescriptive AI models into enterprise processes for decision support and efficiency gains.
  
• Apply ML, deep learning, and NLP techniques to diverse datasets, building scalable, secure data pipelines for AI training, inference, and monitoring.
  
• Collaborate with product managers, engineers, and domain experts to embed AI solutions into operations.
  
• Define, track, and report KPIs to measure productivity improvements, cost savings, and accuracy gains.
  
• Validate AI impact through experimentation frameworks such as A/B testing and performance benchmarking.
  
• Document workflows, models, and processes to ensure knowledge sharing and adherence to best practices.
  
• Stay current on emerging AI frameworks and LLM‑based automation, prototyping innovative solutions for rapid adoption.
  
• Communicate complex technical concepts clearly to technical and non‑technical stakeholders, fostering cross‑functional collaboration.
  

This is a hybrid position. Expectation of days in the office will be confirmed by your Hiring Manager.

Relocation assistance is not provided for this role.

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• 2 or more years of work experience with a Bachelor’s Degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD).
  

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• 3 or more years of work experience with a Bachelor’s Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD).
  
• 2+ years of hands‑on work experience with process/workflow automation and experience deploying Agentic AI solutions.
  
• Advanced Degree with specialization in AI, Computer Science, Data Science, Engineering, Statistics or a highly quantitative field.
  
• Strong technical proficiency in machine learning and AI frameworks, including TensorFlow, PyTorch, scikit‑learn, and Hugging Face Transformers.
  
• Experience with agentic AI and orchestration tools such as LangChain, LlamaIndex, or similar frameworks for multi‑step task automation.
  
• Solid data engineering skills, including SQL, Spark, Databricks, Airflow, Kafka, and ETL/ELT pipeline development.
  
• Proficiency in Python (primary) and familiarity with Java, Scala, or R.
  
• Experience with cloud and MLOps practices, including CI/CD, model monitoring, retraining pipelines, and containerization (Docker, Kubernetes).
  

Work Authorization: Permanent Authorization to work in the U.S. is a precondition of employment for this position. Visa will not sponsor applicants for work visas in connection with this position.

Work Hours: Varies upon the needs of the department.

Travel Requirements: This position requires travel 5‑10% of the time.

Mental/Physical Requirements: This position will be performed in an office setting. The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers.

Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.

Visa will consider for employment qualified applicants with criminal histories in a manner consistent with applicable local law, including the requirements of Article 49 of the San Francisco Police Code.

U.S. APPLICANTS ONLY: The estimated salary range for a new hire into this position is 137,400.00 to 193,750.00 USD per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job‑related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity. Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401(k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program.

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

Granite delivers advanced communications and technology solutions to businesses and government agencies throughout the United States and Canada. We provide exceptional customized service with an emphasis on reliability and outstanding customer support and our customers include over 85 of the Fortune 100. Granite has over $1.85 Billion in revenue with more than 2,100 employees and is headquartered in Quincy, MA. Our mission is to be the leading telecommunications company wherever we offer services as well as provide an environment where the value of each individual is recognized and where each person has the opportunity to further their growth and achieve success.

Granite has been recognized by the Boston Business Journal as one of the "Healthiest Companies" in Massachusetts for the past 15 consecutive years.

Our offices have onsite fully equipped state of the art gyms for employees at zero cost.

Granite's philanthropy is unparalleled with over $300 million in donations to organizations such as Dana Farber Cancer Institute, The ALS Foundation and the Alzheimer's Association to name a few.

We have been consistently rated a "Fastest Growing Company" by Inc. Magazine.

Granite was named to Forbes List of America's Best Employers 2022, 2023 and 2024.

Granite was recently named One of Forbes Best Employers for Diversity.

Our company's insurance package includes health, dental, vision, life, disability coverage, 401K retirement with company match, childcare benefits, tuition assistance, and more.

If you are a highly motivated individual who wants to grow your career with a fast paced and progressive company, Granite has countless opportunities for you.

EOE/M/F/Vets/Disabled

Job Description

We are seeking a highly skilled and experienced Lead AI Engineer to join our dynamic team. The ideal candidate will excel at identifying and articulating complex business problems, and will develop innovative, scalable, and robust AI/ML solutions to address these challenges. Responsibilities will include designing, building, and deploying enterprise-grade AI systems, specifically focused on:

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• Agentic AI solutions to automate operational processes (e.g., interpreting trouble tickets, performing basic troubleshooting, interacting with online portals, data entry).
  
• Retrieval-Augmented Generation (RAG) and ColBERTv2 pipelines for parsing, indexing, and querying enterprise documents to facilitate answers related to process guidelines, product knowledge, and training materials.
  
• Function calling solutions leveraging Large Language Models (LLMs) to automate and perform precise actions in enterprise workflows.
  
• Developing and applying reinforcement learning strategies to optimize and automate decision-making processes within enterprise operations.
  

This role requires hands-on expertise with model fine-tuning, training pipelines, post-training optimization techniques (e.g., model distillation), classification models, and integrating AI systems within complex enterprise environments.

Duties and Responsibilities

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• Develop and implement AI solutions leveraging fine-tuned Large Language Models (e.g., OpenAI models, LLaMA, Mistral).
  
• Design, develop, and optimize Retrieval-Augmented Generation (RAG) pipelines using advanced vector databases (e.g., FAISS, Pinecone, Milvus).
  
• Build and enhance agentic AI systems utilizing frameworks like LangChain, AutoGPT, or similar automation frameworks.
  
• Deploy scalable ColBERTv2 architectures for semantic retrieval and classification.
  
• Create robust pre-processing and post-processing pipelines to enhance model performance, accuracy, and interpretability.
  
• Collaborate closely with cross-functional teams, including product managers, business stakeholders, data scientists, and software engineers.
  
• Implement best practices in model distillation, quantization, and optimization for deployment in production environments.
  
• Ensure compliance with enterprise-grade security, privacy standards, and data governance practices.
  
• Provide leadership and mentorship to team members, supporting their technical development and career growth through coaching, training, and performance feedback.
  
• Drive timely and successful completion of AI/ML projects by setting clear milestones, tracking progress, removing blockers, and aligning resources
  

Required Qualifications

• 
  
• Bachelor's degree in Computer Science, Data Science, Machine Learning, AI, or related fields; advanced degree strongly preferred.
  
• 5+ years of proven experience developing and deploying production-grade AI/ML systems.
  
• Strong programming skills in Python, familiarity with libraries/frameworks such as PyTorch, TensorFlow, Hugging Face, and LangChain.
  
• Demonstrated expertise with LLM fine-tuning (e.g., LoRA, PEFT), distillation, and model optimization.
  
• Practical experience implementing RAG pipelines with embedding technologies and vector stores (e.g., FAISS, Pinecone).
  
• Proven track record building agentic AI systems capable of interacting with multiple enterprise applications and platforms.
  
• Solid understanding of NLP techniques, Transformer architectures, semantic search, and document retrieval technologies (e.g., ColBERT).
  
• Hands-on experience with reinforcement learning techniques, including designing, training, and deploying reinforcement learning models.
  

Preferred Qualifications:

• 
  
• Master's or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or related field.
  
• Familiarity with cloud-based AI services (e.g., AWS SageMaker, Azure ML, Google Vertex AI).
  
• Experience with containerization (Docker, Kubernetes) and deployment pipelines (CI/CD).
  
• Knowledge of advanced AI frameworks and model inference engines such as Triton Inference Server, TensorRT, and ONNX.
  
• Familiarity with model monitoring, observability tools, and techniques to ensure long-term reliability and performance.
  
• Strong communication and interpersonal skills with the ability to clearly articulate complex technical solutions to non-technical stakeholders.
  
• Experience in regulated industries or environments requiring strict compliance and data governance standards.
  

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

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.

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.

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.