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Mid-level metro ML platform role with broad skills and known enterprise brand drives high competition.
Core ML platform skills are transferable, though logistics and enterprise governance preferences increase specialization.
Explicit 6–8 years plus production LLM, AI governance, and platform experience makes shortlisting strict.
Own and groom the backlog and delivery cadence for AI agent platform pods, translating ambiguous executive intent into actionable epics and acceptance criteria for probabilistic systems.
Run efficient scrum ceremonies, track delivery health metrics, remove impediments, and coordinate cross-pod and partner team dependencies to achieve predictable sprint outcomes.
Provide technical stewardship by partnering on architecture, maintaining AI governance checkpoints, managing platform economics, and running time-boxed POCs with clear decisions.
6-8 years of relevant work experience in technical product ownership, program management, or engineering delivery leadership with at least 2 years owning a backlog.
Experience delivering AI/ML or LLM-based features to production, not just prototypes or pilots.
Role location: Pune or Noida with 3 days per week mandatory onsite work.
Experience with managed agent platforms (e.g., Amazon Bedrock/AgentCore) and AI governance processes is preferred but not strictly mandatory.
Experienced in managing complex AI systems involving probabilistic outputs, agent orchestration, and integration with core product APIs.
Comfortable working hands-on in sprint planning, writing detailed acceptance criteria, and resolving delivery friction in distributed, multi-timezone agile teams.
Strong API literacy and experience with AI application patterns (RAG, tool calling, evaluation frameworks), plus ability to communicate clearly to executives through documentation and reporting.