Principal Software Engineer, Simulation

OpenAI

San Francisco (CA)

On-site

USD 347,000 - 490,000

Full time

14 days+

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Job summary

OpenAI is seeking a Principal Software Engineer to lead the architecture and evolution of the Simulation Platform in San Francisco. You will own a critical interface between research and engineering, building systems, APIs, and patterns that let researchers use agentic coding infrastructure safely in training environments.

This role targets senior backend or infra engineers with strong judgment, product sense for technical users, and the ability to drive execution across teams.

Qualifications

  • Extensive backend or infrastructure experience in fast-moving environments.
  • Strong API design, systems design, and engineering fundamentals.
  • Detail-oriented with a focus on correctness, reliability, and operational quality.

Responsibilities

  • Design, build, and evolve the integration between research harnesses and training infrastructure.
  • Create platforms for LLMs to train and evaluate in simulated environments with realistic axes.
  • Own end-to-end integration surfaces from architecture to rollout and maintenance.
  • Build reliable execution systems for demanding training workloads at scale.
  • Collaborate with research, infra, and platform teams to support new use cases.
  • Design clean interfaces and workflows for highly technical internal users.
  • Prevent technical debt by durable abstractions and clear ownership.
  • Raise the bar for correctness and operational rigor in critical systems.

Skills

Backend systems design
API design
Python
Systems reliability
Cross-functional collaboration

Tools

Python tooling

Job description

Principal Software Engineer, Simulation

Applied AI Engineering - San Francisco

About the Team

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.

About the Role

We're looking for a Principal Software Engineer to lead the architecture and evolution of the Simulation Platform. 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.

In this role, you will
  • 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.
You might thrive in this role if you
  • 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.
Location

This role is ideally based in San Francisco due to the close collaboration required with researchers and applied engineering partners.

Compensation

$347K – $490K

Equal Employment Opportunity

We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.

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