Product Engineer (Mountain View) - 17816

Somewhere•Mountain View, CA

3h•Hybrid

About The Position

We are an applied AI research lab building the data and reinforcement learning environments that power how next-generation AI agents are trained and evaluated. Our work has enabled state-of-the-art reasoning datasets , specialized frontier models , and multi-turn, tool-using agents trained via reinforcement learning . These systems are actively used by leading AI research organizations. By focusing on data-centric AI and RL environment curation , we are building foundational infrastructure for the emerging agent ecosystem — and defining an entirely new product category in AI tooling. We are hiring our first Product Engineer — a rare role that sits directly between frontier AI research and product engineering . You will design and build the tools, interfaces, and infrastructure that make RL environment curation usable, intuitive, and powerful for researchers and engineers. This role is not just about shipping infrastructure — it’s about crafting developer and researcher experiences that turn complex workflows into something clear and enjoyable. You bring the mindset of a builder and the taste of a product designer. You move fast from idea to prototype, but you also know when to slow down and harden systems for production. You care deeply about how software feels to use, not just whether it works. Working directly with a small, senior team, you will shape the platform that environment engineers rely on to build, test, evaluate, and deploy training worlds for AI agents.

Requirements

2+ years of full-stack development experience with strong engineering fundamentals
Proficiency in Python and modern web frameworks
Experience with cloud platforms (AWS or GCP) and distributed systems
Solid understanding of CI/CD , automated testing, and production monitoring
Ability to prototype quickly, then iterate toward production-quality systems
Strong instincts for usability and developer experience, especially for technical users
Comfort making product decisions with incomplete information
Ability to prioritize what to build now vs. what to defer
Experience designing systems that start simple and scale over time
Enjoys working closely with users to understand pain points and validate solutions
Clear communicator who enjoys tight feedback loops
Comfortable working across research and engineering domains
Thrives in small teams with high autonomy and responsibility

Responsibilities

Product & Experience Design
Build intuitive dashboards for uploading, managing, and monitoring RL environments
Design visualization tools that make complex metrics (environment quality, difficulty, training progress) clear and actionable
Turn research workflows into polished, usable product experiences
Full-Stack Engineering
Own the full stack — from database schema and APIs to frontend polish
Develop backend infrastructure for scalable hosting and evaluation of RL environments
Design and implement APIs for programmatic interaction with the platform
Research Collaboration
Work directly with AI researchers to deeply understand their workflows
Translate ambiguous research needs into concrete product features
Iterate quickly with users to validate ideas and improve usability
Production & Platform Foundations
Establish best practices for testing, CI/CD, deployment, and monitoring
Scale systems gradually and thoughtfully as usage and complexity grow
Ensure the platform remains reliable, extensible, and pleasant to work with