USD per year
AI Systems Engineer - Codex Core Agents
About The Team
The Codex Core Agents team builds the agent harness that turns model capability into real-world action. We own the systems around the model: prompting and interpreting model outputs, executing actions safely in real environments, and feeding production experience back into better models and better agent behavior. This team sits close to research and works across the stack: harness, model interaction, inference, sandboxed execution, orchestration, evals, production reliability, and the performance envelope around tokens, latency, cost, capacity, and quality. The harness is open source and increasingly part of how models are trained and evaluated, making this one of the highest-leverage layers in Codex.
About The Role
We’re looking for engineers to build the AI systems that make Codex agents dependable in production. The ideal candidate is an agent-systems builder: hands-on across low-level systems and ML workflows, able to debug Codex behavior end to end across the harness, model behavior, inference/runtime stack, GPU fleet, and product surface. You’ll work with research, infrastructure, and product to design agent harness capabilities, run experiments and ablations across the model + system prompt + harness stack, build frameworks for assessing production agent performance, and turn messy failures into durable improvements.
What You’ll Do
- Design and build the core agent harness and execution loop that lets Codex agents interpret model outputs, use tools, execute code, and complete long-horizon tasks safely.
- Build sandboxing, isolation, orchestration, state, and workflow infrastructure for agents operating in real development environments.
- Develop evaluation, experimentation, and debugging systems that distinguish harness issues, model behavior, inference/runtime issues, and product failures.
- Run ablations across prompts, model-facing interfaces, context construction, tool-use strategies, and harness behavior to improve solve rate,
reliability, latency, and cost.
- Improve observability,
profiling, and diagnostics across the agent stack, from backend systems to inference, GPUs, and fleet capacity.
- Work closely with research to make the harness trainable,
measurable, and useful for improving frontier agentic models.
- Build shared primitives that make Codex faster,
safer, more reliable, and easier for other teams and open-source users to build on.
You Might Be A Good Fit If You
- Have built or operated production systems in distributed systems,
infrastructure, developer tooling, sandboxing, virtualization, cloud platforms, or ML systems.
- Enjoy working across layers: Rust systems code,
Python configuration layers, APIs, agent orchestration, evals, logs/traces, inference behavior, runtime constraints, and user outcomes.
- Have hands-on experience with LLM applications,
coding agents, evals, model deployment, inference, compiler/runtime performance, and developer platforms.
- Care deeply about reliability,
safety, performance, debuggability, and clean abstractions.
- Can debug from evidence and move quickly from ambiguous production failures to practical,durable fixes.
- Want to work close to research while still shipping changes to production
- Strong ownership mindset with ability to lead scoped or multi-team AI systems work.
Bonus Points
- Deep Rust/systems/sandboxing/isolation/platform experience.
- Experience with coding agents/agent harnesses/tool-using LLM systems/model evals/post-training feedback loops.
- Background in compilers/kernels/runtimes/inference optimization/GPU systems/benchmarking/profiling/performance engineering.
- Experience building reliable/security-constrained production infrastructure used by many engineers/users.
- Open-source infrastructure or developer-platform work with strong API/usability focus.
About OpenAI
OpenAI is an AI research/deployment company focused on ensuring general-purpose AI benefits all humanity. They emphasize safety & human needs in AI development. OpenAI is an equal opportunity employer committed to diversity & inclusion. Background checks are conducted consistent with applicable laws including fair chance ordinances. Reasonable accommodations are provided for applicants with disabilities.
Compensation Range
$230K – $385K plus equity; total compensation includes salary,equity,and performance bonuses along with benefits such as medical/dental/vision insurance with employer contributions,HSA accounts,FSA accounts (health/dependent care/commuter),401(k) retirement plan with employer match,Paid parental leave (up to24 weeks birth parents/20 weeks non-birthing parents),medical/caregiver leave (up to8 weeks),flexible PTO for exempt employees/up to15 days annually for non-exempt employees,and13+ paid company holidays plus additional office closures,sick/safe time,Mental health/wellness support,and more.