Frontier AI Research · San Francisco
OpenAI's research training infrastructure powers how our frontier models are trained and evaluated. The Simulation team sits at the intersection between the agentic harness that powers OpenAI's products and the research infrastructure where GPT-next is trained, ensuring that our model's training environment is as realistic as possible.
This team owns the integration layer that connects our production harness capabilities into the training stack. The work is highly cross-functional and high leverage: researchers depend on it to run experiments and evaluations reliably as well as to develop the next generation of harness capabilities. Failures in this surface can materially affect training velocity and correctness.
We're looking for a Principal Software Engineer to lead the architecture and evolution of the Simulation. You'll own a critical interface between research and engineering, building the systems, APIs, and operational patterns that let researchers use agentic coding infrastructure safely and effectively in training environments.
This role is ideal for a senior backend or infrastructure engineer with strong technical judgment, product sense for highly technical users, and the ability to drive execution across multiple teams. The highest-leverage work is building robust infrastructure that supports and accelerates research without compromising engineering quality.
Design, build, and evolve the integration between the Codex harness that powers OpenAI's products and research training infrastructure used for training GPT-next
Build a platform for our LLMs to train and be evaluated in simulated environments that mimic their deployment setting as closely as possible, on every axis: agentic harness, compute substrate, timing, tools, data sources, humans in the loop, and more
Own major integration surfaces end-to-end, from architecture and API design through rollout, operations, and long-term maintenance
Build reliable execution systems that can support demanding training workloads at scale
Partner closely with research, agent, infrastructure, and platform teams to support new training use cases and harness capabilities
Design clean, stable interfaces and workflows for highly technical internal users who move quickly and expect strong ergonomics
Prevent one-off workarounds from becoming long-term technical debt by establishing durable abstractions and clear ownership
Raise the bar for correctness, reliability, operational rigor, and engineering judgment across a critical research-facing system
Have significant experience building and scaling backend or infrastructure systems in fast-moving environments
Bring deep strength in API design, systems design, and engineering fundamentals
Are highly detail-oriented and care deeply about correctness, reliability, and operational quality
Can work directly with demanding technical users while maintaining strong engineering discipline
Have a track record of leading cross-functional technical efforts and creating clarity across organizational boundaries
Bring strong product sense and user empathy for internal platforms and developer tooling
Are motivated by enabling researchers and accelerating their work, rather than doing research yourself
Are proficient in Python and have experience with backend platform engineering; Rust experience is a plus
This role is ideally based in San Francisco due to the close collaboration required with researchers and applied engineering partners.
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
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