Senior Product Manager, AI Garage

Google Google · Big Tech · Hyderabad, Telangana, India

Senior Product Manager for AI Garage at Google, focusing on defining and delivering AI-powered agentic products for HR processes. The role involves shaping AI-native product strategy, writing PRDs for systems with non-deterministic behavior (including fine-tuning and RAG), partnering with researchers on model requirements, pioneering multi-agent execution frameworks, and implementing LLM evaluation systems. Requires deep technical fluency in generative AI and experience launching technical products.

What you'd actually do

  1. Define the multi-year AI-native product goal and technical strategy, mapping rapidly evolving foundational models to consumer breakthroughs that achieve sustainable product-market fit.
  2. Write comprehensive Product Requirements Documents (PRDs) accounting for non-deterministic software behavior, establishing explicit guidelines for system instructions, fine-tuning, Retrieval-Augmented Generation (RAG) ingestion pipelines, and safety classifiers.
  3. Partner with Google researchers and infrastructure engineers to co-design model requirements, optimizing latency, context windows, compute budgets, and token utilization.
  4. Pioneer innovative frameworks for multi-agent execution, asynchronous system tracking, and human-in-the-loop validation to deliver contextual, ambient, and non-chatbot intelligence.
  5. Implement robust Large Language Models (LLM) evaluation systems tracking factual alignment while leading cross-functional alignment with Trust, Safety, Legal, and global Policy teams.

Skills

Required

  • Product management experience
  • Technical product launch experience
  • Generative AI mechanics
  • Defining AI-native product strategy
  • Writing PRDs for AI systems
  • Understanding of fine-tuning
  • Understanding of RAG pipelines
  • Understanding of safety classifiers
  • Experience with multi-agent systems
  • Experience with LLM evaluation systems
  • Cross-functional leadership

Nice to have

  • HR product management experience
  • Designing AI interfaces for latency and failures
  • Designing quantitative frameworks for model performance tracking
  • Grounding accuracy
  • System degradation
  • Hallucination rates

What the JD emphasized

  • AI-powered agentic products
  • multi-agent execution
  • LLM evaluation systems
  • non-deterministic software behavior
  • fine-tuning
  • Retrieval-Augmented Generation (RAG) ingestion pipelines
  • safety classifiers
  • human-in-the-loop validation
  • factual alignment

Other signals

  • AI-powered agentic products
  • foundational models
  • multi-agent execution
  • LLM evaluation systems