Gptzero Ai Detection Jobs in Usa

LHH is seeking a Senior Databricks AI/ML Engineer to join our client's team in a fully remote role based in Seattle, WA. Candidates must live in one of the following states, and be prepared to pass a background check/identity verification process: WA, OR, ID, OH, SC, NC, TX, or FL

LHH has a dynamic and challenging opportunity for a Senior Databricks AI/ML Engineer to join our client's engineering team. This role focuses on building and deploying scalable AI/ML solutions across key areas of the insurance functions, including underwriting, claims, pricing, customer engagement, and fraud detection, with a strong emphasis on Databricks architecture and ecosystem integration. The engineer will collaborate closely with data scientists, actuaries, product owners, and engineers to operationalize models, transforming them into robust, production-grade systems seamlessly integrated into business workflows and enterprise platforms.

Salary & Benefits:

• $150k to $185k annually (depending on location & experience)
• Medical, dental, and vision insurance
• 401(k) plan with employer match
• Vacation time accrues at a rate of 10 days annually, with increases based on a tenure schedule, up to a maximum of 25 days per year.
• PTO included Four (4) personal days are granted immediately upon hire.
• Paid holidays are provided for the eight (8) holidays observed in this role throughout the calendar year.
• Up to ten (10) days of sick leave are granted immediately upon hire (pro-rated based on hire date and full-time/part-time status).
• Additional paid time off is available for bereavement, jury duty, and employee volunteer activities in the community.
• Life and disability insurance

Minimum Qualifications:

• Bachelor's degree in Computer Science, AI/ML, Data Science/Engineering, or related field (or equivalent experience).
• 6+ years experience in ETL pipelines, SQL Server, and production data workflows.
• 3+ years enterprise experience with Azure & Databricks AI/ML, including data analysis and visual analytics.
• 3+ years applying ML algorithms and transforming data science prototypes into production.
• 5+ years experience with CI/CD workflows for ML models and related code.
• Strong SQL, real-time and batch data pipeline development, and unsupervised learning techniques.
• Familiarity with agile methodologies (e.g., Scrum).

Responsibilities:

• Conduct customer workshops to gather requirements and design analytics architectures using Azure and Databricks AI/ML.
• Serve as Databricks Architect, managing workspace design, deployment, and governance across environments.
• Define and implement Databricks Lakehouse architecture and governance best practices.
• Integrate Databricks with Azure services and lead implementation of Databricks SQL, Delta Live Tables, and MLflow.
• Develop and maintain automated MLOps workflows for model deployment, monitoring, and lifecycle management.
• Set up and configure Azure and Databricks infrastructure for AI/ML workloads.
• Review ML model code and analytics scripts for quality and performance.
• Design and build data pipelines and cloud services for monitoring, analysis, and reporting.
• Develop robust ETL workflows using Databricks, Spark, and SQL Server for structured and unstructured data.
• Provide production support and performance tuning for data engineering workflows.
• Optimize complex SQL queries and stored procedures for data processing and business logic.
• Collaborate with cross-functional teams to ensure data quality and support business decision-making.
• Scale and deploy machine learning models to handle large-scale data.
• Feed raw data into models and build deployment pipelines for new models.
• Implement logging, observability, and performance monitoring for AI/ML systems.
• Conduct architecture reviews and performance testing.
• Perform other duties as assigned.

Preferred Qualifications:

• Master's degree in a related field.
• Experience in the insurance industry (Auto, Home, Umbrella) and related AI/ML applications.
• Proficiency with tools/platforms: Azure ML, Databricks, Microsoft Fabric, Synapse, Power BI, Snowflake, and APIs like Azure OpenAI and Cognitive Services.
• Knowledge of streaming frameworks: Apache Kafka, Azure Event Hubs, Delta Live Tables.
• Strong math, problem-solving, and rapid learning skills.
• Excellent communication, organization, and independent work capabilities.
• Service-oriented mindset with ability to handle ambiguity and build strong relationships.

Equal Opportunity Employer/Veterans/Disabled

To read our Candidate Privacy Information Statement, which explains how we will use your information, please navigate to Company will consider qualified applicants with arrest and conviction records in accordance with federal, state, and local laws and/or security clearance requirements, including, as applicable:

• The California Fair Chance Act

• Los Angeles City Fair Chance Ordinance

• Los Angeles County Fair Chance Ordinance for Employers

• San Francisco Fair Chance Ordinance

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 .

Hands-On Product Manager — AI-Native Recruiting Platform (HireHQ)

Build the AI operating system for recruiting.

HireHQ is building the next generation AI-native recruiting platform — one that eliminates manual recruiter workflows and replaces them with intelligent automation, AI copilots, and decision intelligence.

Traditional ATS platforms were built for record keeping.

HireHQ is building a recruiting operating system that helps companies find, evaluate, and hire the best talent faster.

We are looking for a highly hands-on Product Manager who can help design and ship this future.

This is not a traditional PM role. You won’t just write tickets and manage roadmaps.

You will:

• Prototype product ideas yourself
• Use AI tools to rapidly build concepts
• Work directly with engineers
• Drive automation across recruiting workflows
• Ship AI-native features quickly

If you like building products at the intersection of AI, automation, and recruiting, you’ll thrive here.

What You'll Work On

You’ll help build core capabilities of the HireHQ recruiting platform, including:

AI Candidate Discovery

• AI-powered candidate search
• Intelligent candidate matching
• Automated candidate enrichment
• Talent graph and candidate insights

AI Screening & Evaluation

• Resume and profile understanding
• AI candidate scoring and ranking
• Interview intelligence and summarization
• Automated screening workflows

Recruiter Copilots

• AI recruiter assistants
• Automated outreach generation
• Pipeline prioritization
• Smart next-action recommendations

Candidate Experience

• AI-powered communication
• Automated follow-ups
• Interview scheduling automation
• Candidate journey insights

Recruiting Automation

• Workflow orchestration across the hiring pipeline
• Intelligent routing and task automation
• AI-driven pipeline management
• Recruiter productivity tools

Our goal is simple:

Reduce manual recruiting work by 80% while improving hiring outcomes.

What You'll Actually Do

You will operate like a product builder.

Ship Products

• Own product areas end-to-end
• Work directly with engineers to design solutions
• Move from idea → prototype → shipped feature quickly

Prototype With AI

You’ll actively use tools like:

• Cursor
• GitHub Copilot
• Claude
• ChatGPT
• Figma

to rapidly create:

• product mockups
• workflows
• prototypes
• PRDs
• user stories
• experimentation plans

We expect PMs to use AI as a force multiplier, not just write docs.

Design AI-Native Workflows

You'll help design product systems that use:

• LLMs
• semantic search
• embeddings
• candidate matching
• summarization
• automation engines

to eliminate manual recruiting work.

Drive Automation

You will constantly ask:

"Why is a human doing this?"

Then build systems that automate it.

Work Extremely Closely With Engineering

You will collaborate daily with engineers to:

• shape product architecture
• refine technical tradeoffs
• ship features quickly
• iterate with real customer feedback

What We're Looking For

Experience

• 5+ years in product management
• Experience building recruiting or HR tech products

Examples include:

• Applicant Tracking Systems (ATS)
• Recruiting CRM platforms
• Candidate engagement tools
• Talent sourcing platforms
• Interview platforms
• Talent intelligence platforms

You deeply understand how recruiting actually works.

AI Product Thinking

You’ve helped build or design AI-enabled product capabilities, such as:

• candidate matching
• screening automation
• workflow automation
• recommendation systems
• AI copilots
• search and ranking systems

Builder Mindset

You like creating things, not just planning them.

You are comfortable:

• prototyping ideas
• creating workflows
• building product concepts independently
• using AI tools to accelerate execution

Comfort With Ambiguity

This is a startup environment.

You should enjoy:

• fast iteration
• unclear problems
• ownership
• shipping quickly

Strong Candidates Often

• Previously worked at HR tech or recruiting tech companies
• Have built ATS or recruiting workflow products
• Use AI tools daily for product development
• Think about automation and workflow intelligence
• Care deeply about shipping useful products quickly

What Success Looks Like

Within your first 3 months:

• Recruiters using HireHQ spend dramatically less time on manual tasks
• AI features automate key recruiting workflows
• Customers rely on AI insights to prioritize candidates
• Recruiters move from administrative work → strategic hiring

Why This Role Is Different

Most recruiting software was designed 15–20 years ago.

HireHQ is rebuilding recruiting software from the ground up using:

• AI agents
• workflow automation
• intelligent candidate matching
• recruiter copilots

This role is an opportunity to help build the AI operating system for hiring.

Title: Lead Software Engineer - AI Application Platform

Mode of interview 1 round in person

Location: Must be in Charlotte, NC to work Hybrid Model

Main Skill set: Python, AI and Angular

Description:

Lead Software Engineer - AI Application Platform

The Opportunity

We are seeking a Lead Software Engineer to guide the architectural development and execution of the client, a sophisticated AI-powered application generation platform. This role suits a proven technical leader with deep, hands-on expertise across the full software stack who finds enabling a team to build better software deeply satisfying.

You will shape critical systems, mentor senior and junior developers through complex technical decisions, conduct rigorous code reviews across multiple technology domains, and directly influence the platform's trajectory through strategic engineering leadership.

This is for someone who:

• Engages thoughtfully when a junior developer asks targeted architectural questions—because you see an opportunity to shape how someone thinks about systems
• Takes time to explain subtle type-safety issues in code review, understanding that feedback is a teaching moment
• Can present architecture clearly to executives and confidently explain both what we're building and why it matters
• Finds more energy in the code your team ships than in the code you write individually
• Has proven depth across the full stack and a track record of developing engineers into stronger contributors

This is not a single-language codebase. The role requires the ability to make informed decisions on TypeScript design patterns, Python FastAPI architecture, AWS security posture, and Terraform state management in context with one another.

The Platform Challenge

The client is fundamentally a Platform-as-a-Service (PaaS) for dynamic application generation. This differs from building a traditional SaaS product. Rather than building one application, you're building infrastructure that enables users to build their own applications.

What this means architecturally:

• Dynamic Content Generation at Scale: Unlike traditional development where code is fixed, AppGen generates JSON form schemas, validation rules, and UI layouts on demand. The FormBuilder component doesn't know what fields will exist until runtime. The layout engine renders user-designed screens from configuration, not hardcoded templates.
• Multi-Tenant Isolation & Data Segregation: Each user gets their own generated app, potentially deployed to their own AWS environment. The architecture must account for data isolation, namespace management, and cross-tenant security considerations.
• User-Defined Data Structures: Traditional applications are built with predetermined database schemas. AppGen works differently—form structures, field types, and validation rules emerge from user conversations with Claude. This brings engineering challenges: How do you safely execute validation logic that users define? When users modify existing forms that have thousands of submissions, how do you maintain backward compatibility? How do you version schemas?
• Content Rendering, Not Code Generation: Unlike traditional no-code platforms where users drag-and-drop to build, AppGen uses AI instead. Users chat with Claude, Claude generates a form schema, and your platform renders that schema reliably across diverse field types, validation patterns, and workflows. The system renders configurations for immediate use, rather than generating code for later deployment.

Experience that directly transfers:

• You've contributed to or led development of low-code/no-code platforms (visual builders, workflow engines, configuration-driven systems)
• You've worked on SaaS platforms with multi-tenant architecture and understand isolation strategies, rate limiting, and per-customer customization
• You've built dynamic rendering systems that handle unknown/arbitrary schemas at runtime
• You've addressed the unique challenges of treating data configurations as user-created content (form builders, report designers, automation workflows)
• You understand the difference between platform infrastructure and applications built on that infrastructure—and the architectural implications of each

Core Responsibilities

1. Technical Architecture & Systems Thinking (40%)

• Shape architectural decisions across the full stack: How should the component layer handle dynamically generated forms? What's the right approach to validate complex cross-field dependencies in the FormBuilder? What separation of concerns makes sense between the Generator Lambda and the Parent Backend?
• Guide architecture discussions: Help senior developers think through design trade-offs. Should we use NgRx or Angular signals for this feature? When does a new Lambda function become worthwhile given cold-start costs?
• Identify and address system-wide bottlenecks: Work across layers to improve performance. Explore Lambda cold-start optimization, RDS query efficiency, and DynamoDB access patterns.
• Establish patterns and guide consistency: Define coding conventions that work across Python, TypeScript, and Terraform. Help new team members understand the reasoning behind architectural choices.
• What this looks like in practice: You're able to justify architectural decisions with technical reasoning. When someone questions an approach, you can explain the trade-offs you considered. You can write code in multiple languages to validate an approach if needed.

2. Code Review & Technical Guidance (30%)

• Full-stack PR reviews: Review Python FastAPI endpoints and Angular components with equal depth, understanding how they interact.
• Deep technical review: Catch issues thoughtful code review can surface:
• RxJS Observable lifecycle and potential memory patterns in Angular
• Query efficiency and data loading patterns in SQLAlchemy
• Terraform module organization and state management implications
• Type safety and TypeScript coverage gaps
• AWS security and IAM configurations
• Educational feedback: Your code reviews help the team learn. When you identify an issue, reviewees understand not just what changed, but how to think about similar problems in the future.
• Define quality expectations: Work with the team to establish what \"production-ready\" means for this platform and support consistent application of those standards.
• What this requires: Experience reviewing code across teams and multiple languages. You know how to write feedback that resonates—clear, constructive, and focused on helping people improve.

3. Mentorship & Team Development (20%)

• Expand specialist capabilities: Help backend specialists learn to contribute to the forms-engine. Support frontend experts in understanding FastAPI patterns.
• Accelerate junior developers: Pair on complex problems. Explain the reasoning behind patterns like DataState. Connect architectural choices to implementation details and performance implications.
• Identify and address gaps: Recognize when someone is struggling with a technology and provide targeted support—training, pair programming, or guidance through architectural decisions.
• Create growth opportunities: Stretch the team into new areas. A backend engineer working on their first Terraform contribution. A frontend specialist implementing an AWS Lambda authorizer.
• What this requires: Genuine investment in people's growth. You've walked developers through major transitions (generalist to specialist, specialist to full-stack, or into new technology areas). You understand that team strength grows when individuals expand their capabilities.

4. Stakeholder Communication & Technical Leadership (10%)

• Explain to diverse audiences: Translate architectural choices and trade-offs for product managers, executives, and business stakeholders. Connect \"optimizing DynamoDB queries\" to \"improving form submission latency by 30%.\"
• Shape technical direction: Contribute the engineering perspective on feasibility, risk, and what unlocks future capabilities.
• Support release confidence: You understand the code changes, comprehend the risks, and know what to monitor. You can stand behind releases.

Required Qualifications

Technical Skills

Frontend (Production Experience)

• 5+ years of Angular (including handling version migrations, optimizing change detection, and guiding teams through reactive patterns)
• Strong TypeScript skills with generics, discriminated unions, and strict mode
• RxJS depth: You understand hot vs. cold observables, unsubscription patterns, and can identify potential memory issues in reviews
• NgRx state management: You've designed stores at scale, optimized selectors, and evaluated architectural implications
• CSS Grid & Responsive Design: You can assess component hierarchy and layout decisions
• Material Design: You've worked within it and know when and how to extend it

Backend (Production Experience)

• 5+ years of Python (async/await, type hints, data modeling)
• FastAPI production experience: session management, dependency injection, middleware
• SQL and ORMs (SQLAlchemy): You write efficient queries and review them critically
• AWS services: Understanding of Lambda behavior, IAM least-privilege patterns, VPC networking
• REST API design: Versioning, error handling, idempotency
• Testing frameworks: pytest, testing st

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.

Join Our Mission to Bridge the Digital Divide - Through AI!

Position: Programs Manager (AI Curriculum - Higher Ed) - Austin, Texas (Hybrid or Remote)

Salary Range: USD 55,000 - 75,000 annually (with a 3-month probation)

Location: Preference for Austin, Texas; remote possible

Travel: Occasional travel required with reasonable notice and accommodations

About Us

Sustainable Living Lab USA (SLL LLC USA) is part of a global movement, HQ in Singapore, offices in India, Indonesia, Japan, and the USA, to make technology inclusive, accessible, and sustainable. We design and deliver innovative education programs that equip learners with essential digital and AI skills - from US community colleges to grassroots organizations worldwide.

About the Role

We’re seeking a dynamic, articulate, and adaptable Programs Manager (AI Curriculum for HigherEd)to support the global expansion and US localization of our AI education programs.

This role involves delivery, curriculum creation, and program development, ideal for someone confident in discussing AI with non-technical audiences, passionate about learning, and eager to influence AI upskilling’s future. You’ll lead technical Train-the-Trainer (TTT) sessions with professors from community colleges and universities both virtually and in-person helping them develop/integrate technical AI concepts as part of their certifications/degrees.

This role blends delivery, curriculum design, and program development, ideal for a flexible, self-motivated individual with a growth mindset who thrives in ambiguous environments, constantly finding solutions to new problems.

Key Responsibilities

1. AI Programs Training & Facilitation (TTT Model)

• Lead virtual and in-person technical Train-the-Trainer (TTT) workshops across US, supporting partners in vocational education and workforce institutions worldwide.
• Ensure participants understand the content and are equipped to customize it for local contexts and learner needs.
• Develop and implement standardized training regimens and SOPs tailored for cross-cultural, regional, and state-wide implementation partners.
• Translate core AI, ML, DL, and Python concepts into engaging, beginner-friendly lessons sensitive to language diversity and digital fluency levels - but also able to deliver technical concepts like Maths for AI, Data science, and Agentic AI topics in depth.
• Conduct engaging and informative training sessions utilizing a standardized curriculum.

2. US Programme & Business Development (SMEs, Colleges, Universities, K12, communities)

• Manage the continuity and expansion of SLL's US programs, particularly within its extensive network of 140+ community colleges and universities spanning 40+ states.
• Work with the team to position SL2 as a leading partner in AI and emerging tech education for the US community college and vocational sector.
• Scale educational programs with school districts, community colleges, and universities, focusing on out-of-school programs and boot camps.
• Scale AI Community Engagements with clubs, societies, and foundations.
• Identify and articulate compelling use-case stories for workforce development partnerships.
• Support engagements with colleges, government agencies, and employers to co-develop bespoke AI education pathways.

3. Content Development and Productization

• Collaborate with internal teams to evolve and update existing programs and co-create new offerings.
• Lead the creation of slide decks, training decks, and other content as a core part of the role.
• Contribute to productizing key experiential learning offerings such as hands-on coding challenges and platform-based simulated work experiences.
• Help localize material for US-based institutions, aligning with skills frameworks and employer demand.
• Co-deliver experiential coding/skilling events, ensuring the core product is designed for global scalability and is adaptable to various educational levels, including tailoring project focus for different competitions for community college and university students.

What We're Looking For

• HigherEd/SME Training Experience: Minimum of 3 years in Higher Ed, training, or facilitation working with HigherEd/SMEs, including at least 2 years focused on technical or digital skills. Experience working across cultures and time zones is highly valued.
• Tech & Learning Aptitude: Intermediate to high knowledge of Python and AI/ML/DL/Agentic AI/Maths for AI/Data concepts. Strong personal interest in the evolving AI landscape and comfort with explaining complex topics to beginners. Experience or enthusiasm for Vibe Coding, digital hackathons, or collaborative prototyping is a plus.
• Communication & Facilitation: Fluent, clear-spoken English and strong public speaking skills. Able to adjust tone, pace, and clarity based on audience (e.g., teachers vs. college professors vs. workforce leaders). A strong presence on MS Teams/Zoom or in person - whether running a classroom session, hackathon, or partner presentation.
• Mindset & Tools: Adaptable, self-motivated, and collaborative. Skilled in using tools like Zoom, Google Workspace, and Teams, and eager to learn new platforms and facilitation techniques.
• Location & Eligibility: Preference for candidates based in Austin, TX, but open to strong remote applicants. Must be authorized to work in the US.

Why Join Us?

• Make Global Impact: Empower teachers and workforce educators across continents to teach AI confidently and contextually.
• Shape the Future of the US Workforce Skilling: Co-create impactful AI programmes for colleges and workforce partners across the US.
• Creative & Collaborative Culture: Work with a mission-driven team that values experimentation, equity, and lifelong learning.
• Featured Benefits: Medical insurance (100% employer contribution), 14 days annual leave, 14 days medical leave, and paternity and maternity leave. We request that the candidate to have their own device.

Ready to Apply?

Send your resume and a short, authentic cover letter to with the subject line: “Programs Manager (AI Curriculum) - U.S.” Please write authentically, and use AI tools with discernment.

Please include:

• Your expected monthly salary in USD
• Your current location and time zone
• Your availability to start
• Any accommodation requests (if applicable)

SLL LLC USA is an Equal Opportunity Employer. We celebrate diversity and are committed to building an inclusive workplace. If you need accommodations during the application process, please let us know.

** We will only consider applicants who are currently residing in South Florida**

About MMG

MMG Equity Partners is a Miami-based, family-led real estate investment and development platform with a portfolio of retail shopping centers across South Florida. Beyond the real estate business, MMG operates a private family office that manages investments, insurance, and financial reporting across multiple entities and family members. MMG separately owns Tamarack Resort in Idaho. We are a flat, fast-moving organization where you will work directly with principals — not layers of management.

This is a ground-floor role. We are building the function from scratch. The right person will define what AI means at MMG, then build it.

The Role

The Director of AI Initiatives & Adoption is responsible for identifying, implementing, and managing AI tools and systems that meaningfully improve how MMG operates across real estate and family office functions. Every project you take on must connect to a business outcome — faster decisions, better data, more deals, reduced overhead.

You will own four things: identifying where AI creates real value at MMG, building or procuring the tools to capture that value, driving adoption across the team and continuously improving how those tools are used, and ensuring the systems are secure and maintainable. Implementation without adoption is not success.

• Reports to Managing Director
• Direct reports - contractors and freelancers as needed
• Current IT Enviroment - outsourced IT for network support

Current Tech Stack (what you are walking into)

You need to understand these systems deeply. Part of your job is figuring out how to connect them and leverage AI to make us more productive/competitive

What you will work on

Below are four areas where we believe AI creates the nearest near-term value at MMG. You first job is to work with the leaders in each area to assess each, prioritize, and build a 6-month roadmap. In addition to the below, the right individual will identify a myriad of other AI use cases to add value and reduce repetitive tasks.

1. Leasing and Tenant Prospecting

MMG owns retail shopping centers and is responsible for filling vacancies with the right tenants – while we work with third party leasing firms, we wish to supplement their efforts by generating direct leads.

• Design and build AI scraping tools to compile databases of South Florida retailers and service businesses for targeted uses
• Build a tool to identify prospective uses/tenants: given a vacancy (size, location, co-tenancy, demographics), which business types and specific operators are the best candidates?
• Design and build AI-assisted leasing outreach workflow: targeted uses identified for vacancies → database queried → outreach drafted and sent → responses tracked in Dynamics (or other CRM)
• Activate Microsoft Dynamics (or other) as the CRM for online leasing
• Identify tools or workflows to monitor existing tenant health (sales reporting, foot traffic, business review signals) to get ahead of vacancies before they happen
• Identify and implement AI-assisted lease abstracting tool to best fit our environment

2. Real Estate Acquisitions

MMG evaluates potential acquisitions across South Florida. Today this process is manual and dependent on individual knowledge. AI can accelerate every stage.

• Design and build AI scraping tools to compile databases of South Florida real estate owners
• Build an AI-assisted underwriting workflow that pulls property data, comps, and market context into a structured analysis template
• Identify AI tools for market intelligence — rent growth trends, cap rate movements, retail category performance by submarket
• Evaluate AI-powered deal sourcing tools (e.g. CoStar integrations, off-market sourcing platforms

3. Private Family Office

MMG's family office manages investments, insurance, and financial reporting for family members. This is a sensitive area requiring strict data governance — but it also has high-value AI applications.

• Addepar AI integration: explore ways to use AI to generate plain-language investment performance summaries and financial reports from Addepar data, reducing manual reporting time
• Insurance management: build a structured database or AI assistant for tracking insurance policies (G/L, personal property, family member policies) with renewal alerts and coverage gap analysis
• Document intelligence: connect family office files in SharePoint to an AI interface for on-demand retrieval of partnership agreements, tax documents, and legal filings
• Evaluate data governance and access controls for family office data — this is sensitive personal and financial information; AI access must be role-based and audited

IT Infrastructure and Security

You are not a network administrator — we have an outsourced IT firm for that. But you are responsible for AI governance at MMG: ensuring every AI tool introduced into the environment meets a clear security and accountability standard.  Practically, this means:

• Evaluating AI vendors for data handling practices — what data leaves our environment, where it is stored, and how it is used for model training
• Defining and enforcing a data classification policy: what information can be sent to external AI APIs, what must stay on-premise or in private cloud environments
• Working with IT firm to ensure AI tools are deployed within the MS365/Azure security perimeter where possible
• Evaluating the Claude Teams → Claude Enterprise migration and the Microsoft Connector configuration for SharePoint access — specifically, controlling which documents are accessible to AI and by which users
• Vetting any third-party AI integrations (i.e. ZoomInfo, Yardi, etc.) for compliance with firm data policies

Prompt Library & AI Adoption

Building the tools is only half the job. The other half is making sure the team actually uses them — and uses them well. This requires two ongoing responsibilities that most AI roles underestimate.

Prompt Library

You will build and maintain a living prompt library — a curated set of tested, optimized prompts for every recurring AI task at MMG. Examples include: underwriting analysis from a rent roll, lease abstraction for a specific clause type, tenant outreach drafts by use category, and insurance renewal gap analysis. The library lives in SharePoint, is accessible to the full team, and is updated continuously based on user feedback and evolving business needs. A well-maintained prompt library is what turns AI from a tool that one person uses well into a capability that the whole organization depends on.

Adoption Monitoring & Continuous Improvement

You are responsible for whether AI tools actually get used — not just whether they get deployed. This means tracking adoption across the team, identifying where workflows are not sticking, providing training and troubleshooting support to staff using AI tools, and iterating on both the tools and the prompts based on real usage patterns. You will serve as the primary internal resource for the team when they hit limitations or need guidance on how to get better outputs. Deployment without adoption is a sunk cost.

What we are looking for

Required:

• 3–6 years of experience in data, technology, or AI — ideally in a context where you had to figure things out without a large team around you
• Hands-on experience with AI tools and LLM platforms — not just using them, but building workflows, prompts, and integrations on top of them
• Demonstrated ability to connect AI capabilities to specific business outcomes (not just technology for its own sake)
• Comfort with the Microsoft 365 ecosystem — SharePoint, Dynamics, Teams, Azure
• Ability to manage and direct contractors and developers without being the one writing all the code
• Non-technical stakeholder communication — you will regularly present AI recommendations, tool evaluations, and implementation roadmaps directly to the principal(s) who are real estate operators, not technologists. The ability to translate AI capabilities into business outcomes (not feature lists) is non-negotiable. If you cannot explain why a tool matters in terms of time saved, deals sourced, or risk avoided, you will not be effective in this role
• In-office presence at Pinecrest HQ is required initially (possible hybrid in the future)

Preferred

• Experience in commercial real estate, property management, or a related field
• Familiarity with Yardi, Addepar, or similar platforms
• Background that includes both technical work (building things) and strategic work (recommending what to build)
• Experience implementing AI in a small-team / resource-constrained environment

GENERAL SUMMARY:

The Manager of AI Enablement (Senior) leads the development and execution of Element Care’s internal approach to artificial intelligence. This role defines AI standards, policies, and best practices while enabling staff across the organization to adopt AI safely, ethically, and effectively. Reporting to the IT department, this position acts as a trusted advisor to leaders and end users, shaping AI governance, vendor strategy, training, and enterprise enablement.

ESSENTIAL RESPONSIBILITIES:

•    Define and maintain organizational AI standards, policies, and governance frameworks.

•    Lead the deployment of off-the-shelf AI solutions, including ambient documentation, predictive analytics, administrative automation, and clinical decision support tools.

•    Enable responsible use of generative AI across administrative and operational functions.

•    Conduct continuous workflow analysis to identify automation and AI-enablement opportunities.

•    Evaluate AI and AI/ML models, tools, and vendor solutions for suitability, risk, and value.

•    Partner with IT, data, analytics, and platform teams to align AI initiatives with enterprise architecture.

•    Provide oversight and guidance on AI-enabled workflows, automation, and agent capabilities.

•    Measure, monitor, and report on AI initiative outcomes, value realization, and performance.

•    Build business cases and recommendations for future AI investments.

•    Serve as the primary advisor to leaders and teams on AI use cases, risks, and governance.

•    Monitor regulatory, ethical, and industry developments related to AI.

•    Help establish and mature a scalable AI enablement and governance operating model.

•    Influence adoption and consistency without direct authority.

•    Perform other duties as assigned.

JOB SPECIFICATION:

•    6–10+ years of relevant professional experience, including applied AI, automation, analytics, or emerging technology leadership.

•    Demonstrated experience evaluating AI/ML models, vendor solutions, or AI platforms.

•    Experience with vendor management, solution selection, or hands-on implementation required.

•    Demonstrated experience defining standards, policies, or enterprise enablement programs.

•    Healthcare or other regulated industry experience strongly preferred.

•    Strong understanding of applied AI, AI/ML evaluation, governance, risk, and ethical considerations.

•    Ability to translate complex concepts into practical organizational guidance.

•    Experience developing business cases and value narratives for technology investments.

•    Executive-level communication and facilitation skills.

•    Proven ability to operate independently and influence across the enterprise.

•    Strategic mindset with a pragmatic, implementation-oriented approach.

Compensation details: 13 Yearly Salary

PI71b2d5685c13-3631

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.

• 
  
• 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.

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

• 
  
• 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.

Job Summary
HellermannTyton North America (HT NA) is accelerating the use of Artificial Intelligence to unlock capacity, improve quality, and fuel growth across North America. As the AI Program Manager, you will build and run a program of AI initiatives that create efficiencies by automating repetitive tasks and removing process waste. You will partner with Operations, Sales, Marketing, IT, HR, and Finance to select the right problems, deliver measurable outcomes quickly, and scale wins across plant sites to increase revenue, reduce cost, and eliminate waste. This will be achieved while maintaining HellermannTyton's Quality and EHS certifications by supporting all corporate policies, procedures, work instructions, and required documentation.

What You'll Do

Opportunity Discovery

• 
  
  
• Conduct stakeholder interviews to capture business objectives and constraints; translate high-level goals into clear, actionable AI project requirements.
  
  
• Build simple business cases with the respective departments; baseline current performance, and quantify benefits
  
  

Program Management

• 
  
  
• Work with Business Stakeholders to prioritize initiatives by value, impact, labor hour avoidance, and risk mitigation.
  
  
• Prioritize AI program and project roadmap into short, iterative deliverables; prioritize delivery based on business impact and feasibility.
  
  
• Run stage-gated delivery (scope pilot scale) aligned to HellermannTyton COE project governance; set decision forums, risk controls, and incremental results.
  
  
• Work with Business and IT to develop data and IT infrastructure and tools to support AI program roadmap.
  
  

Delivery

• 
  
  
• Ensure ownership of agents and AI workflows are transitioned to business stakeholders within the business.
  
  
• Engage with change management to ensure AI projects are accepted, and AI becomes integrated into processes such that AI becomes "the way we work."
  
  
• Make value visible and auditable. Track and report on program benefit metrics such as savings, improved experience, reduced waste, efficiency improvements, etc.
  
  
• Share AI knowledge to upskill the organization. Coach stakeholders to see AI use cases in the processes.
  
  

Governance

• 
  
  
• Partner with Legal/HR on data privacy and AI use policies.
  
  
• Ensure solutions comply with IT corporate cybersecurity and risk guidelines.
  
  

Success in this role will require:

• 
  
  
• Collaboration & Communication
  
  
• Adaptability
  
  
• Problem Solving
  
  
• Analytical Thinking
  
  
• Business Acumen
  
  

What You'll Bring

• 
  
  
• Bachelor's degree in Project/Program Management, Engineering, Manufacturing, Computer Science, Data/Analytics, or related field.
  
  
• 3+ years leading data/AI/automation programs with manufacturing operations; proven track record delivering hard dollar benefits and labor hour avoidance.
  
  
• Mastery of program management (business cases, roadmaps, stage gates, financials).
  
  
• Excellent stakeholder communication and leadership across Operations, Sales, Marketing, IT, HR, and Finance.
  
  

Preferred Qualifications

• 
  
  
• Background manufacturing or associated environments.
  
  
• Lean / Six Sigma certification; experience embedding AI within continuous improvement programs.
  
  
• Experience with AI Tools (MS CoPilot Studio, MS Fabric, MS Azure Foundry)
  
  

By applying for a position with HellermannTyton, you understand that should you be made an offer, it will be contingent on your undergoing and successfully completing a background check through the use of our 3rd party supplier. Background checks may include some or all of the following based on the nature of the position: SSN/SIN validation, education verification, employment verification, criminal check, driving history, and drug test. You will be notified during the hiring process of which checks are required by the position.

HellermannTyton Corporation is an Equal Opportunity Employer and does not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class.