Product Owner – AI/ML

We are seeking a Product Owner to lead the vision, prioritization, and execution of cutting-edge agentic AI initiatives. This role is focused on end-to-end product ownership driving autonomous, intelligent AI systems from concept to delivery. The ideal candidate will have strong experience in managing AI/ML products and a clear understanding of how to create value through intelligent agents, LLM-based automation, and ML workflows.

• Define and communicate the product vision for agentic AI systems, enabling intelligent, autonomous behavior across business-critical workflows.
• Own and maintain a well-prioritized product backlog, translating strategic goals and stakeholder needs into actionable user stories and epics.
• Collaborate closely with ML engineers, data scientists, software developers, and data engineers to ensure delivery aligns with technical feasibility and business impact.
• Drive development of AI features involving multi-agent orchestration, self-improving systems, tool-use, planning, and decision-making capabilities.
• Act as the primary liaison with stakeholders, gathering feedback, defining KPIs, and iterating on features to ensure continuous product improvement.
• Partner with MLOps, data, and engineering teams to align on system architecture, deployment strategies, and compliance for scalable AI delivery.
• Monitor progress and product health using appropriate metrics (e.g., adoption, latency, reliability, model performance).
• Contribute to go-to-market planning, user adoption strategies, and internal enablement for AI-driven features.
• Stay updated on trends in agentic AI, LLM toolchains, open-source agent frameworks (LangChain, AutoGPT, LangGraph, etc.), and bring those insights into product strategy.

• 5+ years of experience in product management or product ownership, preferably in AI/ML-driven software environments.
• Proven track record of delivering successful AI/ML or intelligent automation products, ideally involving LLM-based agents, decision engines, or workflow orchestration.
• Strong understanding of the AI/ML development lifecycle, including data ingestion, model training, validation, deployment, and monitoring.
• Familiarity with modern AI agent architectures (planning, memory, tool use), and platforms like LangChain, AutoGPT, CrewAI, LangGraph, or custom agent stacks.
• Experience working in Agile teams, coordinating across cross-functional roles (engineering, data science, UX, business).
• Strong analytical and communication skills capable of making trade-offs, defining MVPs, and translating complex technical work into user and business value.
• Comfort working with tools like Jira, Confluence, or similar backlog management platforms.