What are the responsibilities and job description for the AI Product Owner - W2 Only position at Saransh Inc?
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. escalate 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
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. escalate 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