We’re a new research lab in San Francisco, currently focused on developing new foundational capabilities for enabling useful AI agents. We’re pursuing several key research bets that will enable AI agents to perform real-world actions, learn from human feedback, self-course-correct, and infer our goals. In particular, we are really excited about the work in combining large language models (LLMs) with reinforcement learning (RL) to solve reasoning and planning, learned world models, and generalizing agents to physical environments. Our work builds on that of Amazon’s broader AGI team, which recently introduced Amazon Nova, a new generation of state-of-the-art foundation models (FMs).

We’re a small, talent-dense team with the resources and scale of Amazon. Each team in the lab has the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research. We’re entering an exciting new era where AI agents are the next playing field; the right research bets can reinvent what’s possible with AI. We’d love for you to join our new lab and build it from the ground up!

Key job responsibilities
The Product Manager - Technical role for the AGI Autonomy Lab focuses on defining and prioritizing tooling roadmaps that support data collection, model evaluation, and release processes, balancing custom builds. You will bridge research and engineering by translating complex technical needs from researchers into actionable product requirements, ensuring tools address real-world bottlenecks and scale workflows.

Key qualifications include:
- Deep proficiency in Large Language Models (LLMs), including hands-on implementation, prompt engineering, and integration into complex systems
- Ability to translate LLM capabilities into product roadmaps that accelerate research velocity
- Experience building products for technical audiences (e.g., AI/ML tools)
- Ability to thrive in ambiguous research environments

This role offers opportunities to impact Amazon’s ecosystem across retail, logistics, and consumer products, with access to AWS resources and deployment to billions of users.