Applied AI Engineer, Codex Core Agent

Location

San Francisco; London, UK; New York City; Seattle

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.

More details about our benefits are available to candidates during the hiring process. This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

OverviewApplication

About the Team The Codex Core Agent team builds the kernel of Codex. We own making the agent better, accelerating research, and making those improvements real in production for our users. That means working across the systems that make Codex actually function as an agent in the real world: the production performance envelope around tokens, latency, reliability, cost, and capacity; the core execution loop and interfaces that turn models into useful behavior; the shared infrastructure that enables other teams to build on Codex; and the feedback loops that turn real-world usage into better models and better agent behavior over time. About the Role We’re looking for applied AI engineers to help bring Codex agents from impressive demos to dependable tools. This role is about improving agent performance on real software engineering tasks and closing the gap between research capability and real-world usefulness. You’ll work closely with research, infrastructure, and product to ensure agents are not just powerful but useful steerable and reliable in practice. The job is not only to improve model behavior in isolation but to turn those improvements into measurable gains in solve rate usefulness and economic value for users. What You’ll Do

• Design and iterate on agent behaviors across real-world coding tasks and long-horizon workflows.
• Work closely with research to develop and run evals to measure agent performance regressions failure modes and edge cases.
• Improve performance through prompting tool-use strategies context construction and model-facing experimentation.
• Analyze failures in production and systematically improve robustness and reliability.
• Build feedback loops and data systems that get better real-task data into evaluation and research.
• Work with product teams to shape user-facing agent experiences and the interfaces the agent depends on.
• Help define what “good” looks like for agents completing complex tasks end-to-end.

You Might Be a Good Fit If You

• Have experience building or shipping machine learning or LLM-powered products.
• Are strong in Python and comfortable with modern ML tooling.
• Have worked on model evaluation fine-tuning or prompt design.
• Think in terms of systems and user outcomes not just model metrics.
• Enjoy debugging messy real-world failures and turning them into improvements.
• Want to work in the layer that turns research and model potential into systems that actually work for users.

Bonus Points

• Experience with agent frameworks or tool-using LLM systems.
• Research experience with code generation models or developer tooling.
• Experience working with large messy datasets or production logs.

Remote Work Allowance

No explicit mention of remote work allowance is present in this job posting.

Skills Mentioned (from Responsibilities & Qualifications)

Skills:

• Machine learning / LLM-powered product development experience
• Python programming proficiency
• Modern ML tooling familiarity
• Model evaluation
• Fine-tuning
• Prompt design
• Debugging complex real-world failures
• Systems thinking focused on user outcomes
• Experience with agent frameworks or tool-use strategies (bonus)
• Research experience with code generation models or developer tooling (bonus)
• Handling large datasets or production logs (bonus)

Experience Level

Not explicitly stated inferred mid-to-senior level given responsibilities such as designing agent behaviors across complex workflows working closely with research teams improving robustness in production environments shipping ML/LLM-powered products debugging complex failures shaping user-facing experiences involvement in fine-tuning/model evaluation.