AI Systems Engineer, Codex Agents
AI Systems Engineer · Senior · Full Time
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Role
What you'll do.
OpenAI is seeking a highly skilled AI Systems Engineer for the Codex Core Agents team, focusing on building advanced agent harness systems that transform AI model capabilities into actionable real-world solutions. The ideal candidate will work across multiple technical layers, from low-level systems to ML workflows, to enhance the reliability, safety, and performance of AI agents.
Responsibilities
- Agent Harness Development: Design and build the core agent execution loop enabling Codex agents to interpret model outputs, use tools, execute code, and complete complex tasks safely
- Infrastructure Engineering: Develop sandboxing, isolation, orchestration, and workflow infrastructure for agents operating in real development environments
- Performance Optimization: Run ablations and experiments to improve agent solve rate, reliability, latency, and cost across model interfaces and harness behaviors
- Observability Enhancement: Improve diagnostics, profiling, and observability across the entire agent technology stack from backend systems to GPU inference
- Collaborative Research Integration: Work closely with research teams to make the agent harness trainable, measurable, and useful for improving frontier agentic models
Qualifications
What we look for.
Technical
Systems Programming
Advanced experience with Rust systems code, distributed systems, and low-level infrastructure development
Machine Learning Infrastructure
Hands-on experience with LLM applications, model deployment, inference optimization, and developer platforms
Cloud and Runtime Technologies
Proficiency in cloud platforms, virtualization, sandboxing, and runtime performance optimization
Education
Advanced Technical Degree
Bachelor's or Master's degree in Computer Science, Software Engineering, or related technical discipline preferred
Experience
Production Systems
Demonstrated experience building and operating production systems in distributed computing, developer tooling, or ML infrastructure
Multi-Layer Technical Expertise
Proven ability to work across technical layers including systems code, configuration layers, APIs, orchestration, and runtime constraints
Skills
Required
Rust Programming
Strong systems-level programming skills in Rust
Python
Proficiency in Python for configuration and scripting
Distributed Systems
Deep understanding of distributed computing principles
Preferred
Compiler Design
Nice to haveBackground or experience in compilers, kernels, and runtime systems
GPU Systems
Nice to haveKnowledge of GPU system optimization and performance engineering
Open Source Development
Nice to haveExperience contributing to infrastructure or developer platform open-source projects
Tech stack
Languages
Frameworks
Databases
Tools
Other
Compensation
Pay and benefits.
Base·USD 230,000 – 385,000
Equity·Stock options
Benefits
Equity Compensation
Stock options offering potential additional financial upside
Cutting-Edge Work
Opportunity to work at the forefront of AI systems engineering
Research Collaboration
Close interaction with world-class AI research teams
Process
Interview steps.
- 01
Initial Screening
Technical resume review and initial recruiter conversation
- 02
Technical Interview
Detailed technical assessment of systems engineering and ML infrastructure skills
- 03
Systems Design Challenge
In-depth evaluation of candidate's ability to design complex AI agent systems
- 04
Final Team Interview
Comprehensive discussion with Codex Core Agents team members
Full posting
Original listing.
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 YouHave 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.
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.
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.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
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We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
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