AI Product Owner - W2 Only

Saransh Inc; Louisville (KY); On-site; USD 110,000 - 140,000; Full time

Job summary

Trizetto Products in Louisville, KY seeks an AI Product Owner to define and execute the product vision for agentic AI solutions. You will align strategy with business goals and guide AI initiatives across product, engineering, and governance teams.

The role requires defining requirements, managing the backlog, and driving performance through KPIs while collaborating with UX and data governance to ensure responsible AI practices.

Qualifications

• Proven experience as Product Owner/Product Manager, ideally on AI/ML or automation products
• Experience defining product vision, backlog, and roadmaps for AI solutions
• Cross-functional collaboration with engineering, UX, and governance/compliance teams
• Familiarity with agentic AI concepts and modern AI frameworks is a plus

Responsibilities

• Define and own the product vision, strategy, and roadmap for agentic AI solutions aligned with business objectives
• Own backlog with user stories and acceptance criteria for engineering teams
• Define agent behaviors, decision boundaries, and success criteria (task completion, accuracy, latency, cost)
• Collaborate with business stakeholders, AI/ML engineering, UX designers, and data governance/compliance teams
• Define guardrails, escalation paths, and fallback mechanisms for agent failures or edge cases
• Drive go-to-market planning, pilots, and phased rollouts of agentic AI features
• Run Agile/Scrum ceremonies and manage dependencies across cross-functional teams

Skills

Product Owner

AI/ML experience

Automation products

Job description

Job title: AI Product Owner

Location: Louisville, KY

W2 Position

Name: Large Language Model (LLM)

AI/ML

Trizetto Products

Job Summary

Product Strategy & Vision

Define and own the product vision, strategy, and roadmap for agentic AI solutions aligned with business objectives

Identify high-value use cases where autonomous agents can drive efficiency, automation, or new capabilities

Evaluate build-vs-buy decisions across agentic AI frameworks (LangChain, LangGraph, AutoGen, CrewAI) and LLM providers

Stay current on the evolving agentic AI landscape and translate emerging capabilities into product opportunities

Backlog & Requirements Management

Own and prioritize the product backlog, translating business requirements into clear user stories and acceptance criteria for engineering teams

Define agent behaviors, decision boundaries, and success criteria (task completion rates, accuracy, latency, cost per task)

Specify requirements for agent memory, tool access, multi-agent orchestration, and human-in-the-loop checkpoints

Balance autonomy vs. control determining where agents should act independently vs. upscale to humans

Cross-Functional Collaboration

Act as the primary liaison between business stakeholders, AI/ML engineering teams, UX designers, and data governance/compliance teams

Partner with engineering to scope technical feasibility, effort estimation, and architecture trade-offs for agentic workflows

Work with data science/ML teams to define evaluation frameworks for hallucination rates, task success, and agent reliability

Collaborate with design teams on human-agent interaction patterns and interfaces (chat, dashboards, approval workflows)

Governance, Risk & Compliance

Define guardrails, escalation paths, and fallback mechanisms for agent failures or edge cases

Ensure agentic systems meet responsible AI standards: transparency, auditability, bias mitigation, and data privacy

Partner with legal/compliance teams on risk assessment for autonomous decision-making systems

Establish monitoring and audit trails for agent actions, especially in regulated domains

Launch & Performance Management

Drive go-to-market planning, pilot programs, and phased rollouts of agentic AI features

Define and track KPIs/OKRs: task automation rate, agent accuracy, cost savings, user adoption, time-to-resolution

Analyze production agent performance data to identify improvement opportunities and prioritize iterations

Manage stakeholder communication, demos, and executive reporting on agentic AI product progress

Agile Delivery

Run sprint planning, backlog grooming, and stakeholder demos in an Agile/Scrum environment

Prioritize technical debt, model updates, and framework migrations alongside feature development

Manage dependencies across multiple agent workstreams and cross-functional teams

Required Skills

• Health Care Products , Consumer care product develop , Dx Product Lifecycle Management
• Proven experience as a Product Owner/Product Manager, ideally on AI/ML or automation products
• Trizetto Products