5+ years of experience in product management, ideally in AI/ML software domains.
Proven success in launching AI/ML or intelligent automation products, particularly with LLM-based technologies.
Deep understanding of the AI/ML lifecycle, including data management and model deployment.
Knowledge of advanced AI agent frameworks and architectures like LangChain and AutoGPT.
Experience in Agile methodologies and collaboration across technical teams.
Excellent analytical and communication skills, translating tech into user benefits.
Proficient in backlog management tools such as Jira or Confluence.
Responsibilities
Define and communicate the product vision for agentic AI systems to enable autonomous behavior in workflows.
Maintain a prioritized product backlog, turning strategic goals into actionable user stories.
Collaborate with ML engineers and data scientists to align product delivery with technical and business goals.
Drive AI feature development, focusing on orchestration, self-improvement, and decision-making capabilities.
Act as the main contact for stakeholders, gathering feedback and defining KPIs for product improvement.
Partner with teams on architecture, deployment, and compliance for scalable AI systems.
Track product health and progress using metrics such as model performance and adoption rates.
Influence go-to-market strategies and user adoption efforts for AI-driven features.
Stay informed on trends in agentic AI and integrate findings into product strategy.
Benefits
Opportunity to shape the future of agentic AI systems.
Collaborative environment with cross-functional teams including engineering and data science.
Access to latest tools and technologies in AI and ML.
Contributions to impactful, cutting-edge projects in automation.
Support for continuous learning and professional development in the AI field.
Full Job Description
Key Responsibilities
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.
Required Skills & Experience
5+ years of experience in product management , 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.
