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Generative Ai Project Manager Jobs in Madison, WI

Urus

AI Engineer

Watertown, WI

Strong knowledge of Large Language Models, Generative AI, NLP, and Machine Learning concepts. (3+ ... We set the standard for farm management solutions and fix our eyes on raising the bar to meet the ...

Urus Group LP

AI Engineer

Watertown, WI · On-site +1

Strong knowledge of Large Language Models, Generative AI, NLP, and Machine Learning concepts. (3+ ... We set the standard for farm management solutions and fix our eyes on raising the bar to meet the ...

Farm Systems

AI Engineer

Watertown, WI

Strong knowledge of Large Language Models, Generative AI, NLP, and Machine Learning concepts. (3+ ... We set the standard for farm management solutions and fix our eyes on raising the bar to meet the ...

AgSource

AI Engineer

Watertown, WI · On-site +1

Strong knowledge of Large Language Models, Generative AI, NLP, and Machine Learning concepts. (3+ ... We set the standard for farm management solutions and fix our eyes on raising the bar to meet the ...

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All JobsGenerative Ai Project JobsGenerative Ai Project Manager JobsGenerative Ai Project Manager Jobs in Madison, WI

Generative Ai Project Manager information

See Madison, WI salary details

$38.8K

$103.5K

$163.2K

How much do generative ai project manager jobs pay per year?

As of Aug 7, 2026, the average yearly pay for generative ai project manager in Madison, WI is $103,465.00, according to ZipRecruiter salary data. Most workers in this role earn between $79,100.00 and $123,900.00 per year, depending on experience, location, and employer.

What are some unique challenges faced by generative AI project managers when overseeing cross-functional teams?

Generative AI Project Managers often encounter the challenge of bridging knowledge gaps between technical AI specialists, such as data scientists and engineers, and non-technical stakeholders, like product managers or business leaders. Coordinating clear communication and aligning project goals requires balancing rapid technological changes with business requirements, all while ensuring ethical and responsible AI development. Additionally, managing timelines can be complex due to the experimental nature of generative AI projects, which may involve iterative prototyping and unexpected roadblocks. Building trust and facilitating collaboration across diverse teams is key to project success.

What is the difference between Generative Ai Project Manager vs Data Scientist?

AspectGenerative Ai Project ManagerData Scientist
Required CredentialsProject management certifications, AI knowledgeDegree in Data Science, Computer Science, or related fields
Work EnvironmentCross-functional teams, project planningData analysis, model development
Employer & Industry UsageTech companies, AI startups, R&D departmentsTech firms, research institutions, analytics companies

While both roles involve AI, the Generative Ai Project Manager oversees AI projects, coordinating teams and timelines, whereas the Data Scientist focuses on analyzing data and building models. The project manager ensures project delivery, while the data scientist develops the AI models used within projects.

What does a generative AI project manager do?

A Generative AI Project Manager oversees projects that involve the development and implementation of generative artificial intelligence solutions. Their responsibilities include coordinating teams of data scientists, engineers, and designers, managing project timelines and budgets, and ensuring that deliverables meet business objectives. They also facilitate communication between technical and non-technical stakeholders to ensure alignment and project success. Additionally, they stay updated on advances in AI technology to guide project direction and innovation.

What are the key skills and qualifications needed to thrive as a generative AI project manager?

To thrive as a Generative AI Project Manager, you need a solid understanding of AI/machine learning concepts, project management methodologies, and a relevant degree (such as computer science or engineering). Familiarity with tools like Jira, Agile frameworks, and AI platforms (e.g., TensorFlow, PyTorch) as well as certifications like PMP or Agile Scrum Master are highly beneficial. Strong leadership, communication, and problem-solving skills set outstanding candidates apart by enabling them to bridge technical and non-technical teams. These abilities are crucial for delivering AI projects on time, ensuring alignment with business goals, and adapting to rapidly evolving technology landscapes.
What are popular job titles related to Generative Ai Project Manager jobs in Madison, WI? For Generative Ai Project Manager jobs in Madison, WI, the most frequently searched job titles are:
What job categories do people searching Generative Ai Project Manager jobs in Madison, WI look for? The top searched job categories for Generative Ai Project Manager jobs in Madison, WI are:
What cities near Madison, WI are hiring for Generative Ai Project Manager jobs? Cities near Madison, WI with the most Generative Ai Project Manager job openings:
Generative Ai Project Manager jobs near you
Infographic showing various Generative Ai Project Manager job openings in Madison, WI as of August 2026, with employment types broken down into 88% Full Time, 11% Part Time, and 1% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $103,465 per year, or $49.7 per hour.

AI Engineer

Urus

Watertown, WI

Full-time

Posted 11 days ago

Job description

VAS is seeking an AI Engineer to lead building of scalable real-time production grade applications that use AI/ML models. This is a strategic, hands-on position for an experienced technical leader who has a track record of shipping AI-enhanced customer applications and tooling used by engineering teams.


This role will be focused on embedding LLMs, agent-based systems, and automation into core development workflows-boosting productivity, reducing manual toil, and accelerating delivery, essentially transforming how our engineers build, test, and ship software.

Responsibilities

  • Understand customer challenges and how integrating AI capabilities can help lead to solutions that have AI as a differentiator. 
  • Identify opportunities to apply AI for efficiency, growth, and customer value.
  • Drive awareness of AI capabilities and demonstrate how it can address customer needs, improve efficiency, reduce costs, and drive growth.
  • Drive transformation from AI-Ad Hoc to AI-Native engineering practices.
  • Serve as the AI technical SME, conduct R&D (research and development) to meet the needs of our AI strategy.
  • Continuously assess emerging AI tools and make data-driven recommendations.
  • Measure & Accelerate Adoption: Establish KPIs, track progress from the current to 100% adoption, implement interventions to accelerate uptake and communicate impact.
  • Build Center of Excellence: Create forums for knowledge sharing, celebrate wins, and foster peer-to-peer learning.
  • Establish AI governance frameworks and guardrails covering compliance, security, privacy, and ethical AI practices, and embed them into development workflows.
  • LLM Agents & Prompt Engineering
    • Architect and implement LLM agents.
    • Build composable, tool-augmented reasoning chains (e.g., RAG, CoT, ReAct, planner-executor).
    • Integrate vector databases and knowledge graphs to support retrieval-augmented generation (RAG).
    • Design and maintain high-quality prompt strategies for robustness and reliability.
  • Model Context Protocol (MCP) & Backend
    • Develop and maintain scalable APIs, 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
    • Integrate, deploy, fine tune and monitor models in production using cloud providers.
    • Set up agent logging, observability dashboards, and recovery workflows.
  • Front-end & User Experience
    • Collaborate with front-end developers or build user-facing components using React, TypeScript.
    • Ensure seamless user and agent interaction via UI and API bridges.

Education & Experience Requirements

  • Bachelor of Science in Software Engineering, Computer Science, Data Science, AI/ML or related field preferred.
  • 10+ years of experience in software development and design.
  • Proven experience in AI/ML solution design and hands experience with AI-powered development tools. 3+ years of experience preferred. 
  • Strong knowledge of Large Language Models, Generative AI, NLP, and Machine Learning concepts. (3+ years of experience preferred).
  • Hands-on experience with deep learning frameworks. 
  • Experience with RAG pipelines, vector databases, and agentic frameworks.
  • Familiarity with cloud-based AI services.

For the past 40 years we've woken up each day to support those that never stop feeding the world - and we have no plans to quit. We set the standard for farm management solutions and fix our eyes on raising the bar to meet the next generation of expectations.

Our software and information solutions help collect and connect a farm's data - from herd management to feed performance, tracking and more. These insights are a source of truth, empowering producers and their trusted advisors to make profit-driven and sustainable management decisions.

Whether near or far, large or small, VAS is at the heart of your dairy.

VAS has deep roots in the industry through its origin within the URUS family of companies. As a holding company with cooperative and private ownership, URUS is a family of businesses at the heart of the dairy and beef industry - Alta Genetics, GENEX, Genetics Australia, Leachman Cattle, Jetstream, PEAK, SCCL, Trans Ova Genetics and VAS.  Each organization has its unique identity, products, and services. These companies work globally to provide cutting-edge dairy and beef genetics, customized reproductive services to maximize conceptions, dairy management information to take producers to the frontline of progressive dairy farming, and an array of products and services to help bovines reach their full genetic potential. URUS has 9 brands in 17 retail countries and employs nearly 2,800 people globally.

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