Systems Engineer

AI Systems Engineer - Codex Core Agents Location San Francisco Employment Type Full time Department Applied AI Compensation 230K-385K Offers Equity The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits. Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit) 401(k) retirement plan with employer match Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks) Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law) Mental health and wellness support Employer-paid basic life and disability coverage Annual learning and development stipend to fuel your professional growth Daily meals in our offices, and meal delivery credits as eligible Relocation support for eligible employees Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided. 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, or 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. Still write meaningful code, show strong ownership, and can lead scoped or multi-team AI systems work. Bonus Points Deep Rust, systems, sandboxing, isolation, or low-level platform experience. Experience with coding agents, agent harnesses, tool‑using LLM systems, model evals, or post‑training feedback loops. Background in compilers, kernels, runtimes, inference optimization, GPU systems, benchmarking, profiling, or performance engineering. Experience building production infrastructure used by many engineers or users under demanding reliability and security constraints. Open‑source infrastructure or developer‑platform work with strong taste for APIs and usability. 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. Compensation Range: 230K-385K #J-18808-Ljbffr