Product Owner

Seasoned Product Owner/Product Manager with 7+ years of experience driving Agile full-stack product development, defining product vision and roadmaps, managing AI/LLM-enabled products, leading stakeholder collaboration, backlog prioritization, and agentic AI-driven software delivery across complex enterprise and healthcare environments.

Skills: -

Mandatory skills

· 7+ years of Product Management / Product Owner experience Strong Agile/Scrum product ownership experience

· Experience working with AI/LLM-enabled products Strong stakeholder management and communication skills Backlog management and prioritization expertise Experience defining product vision, roadmap, and user stories

· Desired skills Healthcare domain experience AI, NLP, and sentiment analysis solution exposure Data analytics and reporting experience UX/UI understanding

· Experience with Jira and Agile tools JD Own product vision, roadmap, and delivery priorities. Gather and define business requirements and user stories. Prioritize backlog and manage sprint planning activities.

Collaborate closely with engineering, QA, and business stakeholders. Define AI product requirements involving LLMs, NLP, and text analytics. Drive requirement clarification and acceptance criteria definition.

· Monitor product delivery and ensure alignment with business goals. Facilitate Agile ceremonies and stakeholder communication. Ensure successful product adoption and continuous improvement.

Proven experience architecting and delivering systems using agentic IDEs

· Experience managing Full Stack software product development Understanding of React, APIs, MongoDB, and modern web applications

· Ability to: Define architectural intent that agents can follow, Break features into agent executable tasks, Govern AI autonomy (guardrails, permissions, reviews) • Integrate agentic workflows into CI/CD pipelines Experience supervising AI agents across: • Multi service systems

· Legacy modernization • Large codebases / monorepos Strong understanding of: • Security implications of autonomous code execution • Compliance, auditability, and traceability • AI assisted SDLC operating models

· Core Responsibility: Guide effective use of agentic IDEs for complex, multi-module or cross-service changes

· Establish review practices and quality checks for AI-generated code • Mentor team members on balancing autonomy, correctness, and maintainability in AI-assisted development

· Design system architectures that support AI-augmented and agentic development workflows • Define guardrails, standards, and governance for the use of autonomous coding agents • Evaluate impact of agentic IDEs on SDLC, CI/CD pipelines, security posture, and technical debt