OpenAI

Software Engineer, Codex Security

San Francisco$230k–$325kfulltimemidAdded today

About this role

Join OpenAI's Codex Cyber team to build AI-native application security products that help organizations detect and fix vulnerabilities at scale. You'll own full-stack features spanning user interfaces, backend services, cloud infrastructure, and security analysis pipelines in a fast-moving, early-stage product area.

What you'll do

Build end-to-end product features for Codex Security, from developer interfaces to APIs and backend services
Own 0-to-1 projects across product pods, platform security controls, and deployment workflows
Translate security research and model capabilities into intuitive vulnerability detection and remediation workflows
Design scalable systems for long-running security analyses across large codebases and enterprise environments
Collaborate with product, security research, infrastructure, and customer teams to iterate from real-world feedback
Help shape technical direction and architecture as the Codex Cyber platform grows

What they're looking for

Full-stack software engineering with strong fundamentals
Backend services and cloud infrastructure design
Developer tools and platform experience
Product thinking and technical UX sensibility
Ability to work across ambiguous 0-to-1 projects
Security domain knowledge (application security, vulnerability research, or secure workflows preferred but not required)
Scalable systems design
API and workflow design for technical users

Benefits

Work on cutting-edge AI-native security technology at OpenAI
Early-stage product with significant growth potential and impact
Full-stack ownership across product, platform, and infrastructure
Collaboration with world-class security research and infrastructure teams
San Francisco location

Likely interview questions

Walk us through a time you owned a 0-to-1 product feature from ambiguous requirements to production—what did you do to clarify scope and reduce risk?
Describe your experience building for technical users or developers. How do you balance feature richness with usability?

Tell us about a time you had to integrate complex research or modeling outputs into a user-facing product. What were the challenges?
What experience do you have with security, and how has it influenced your approach to building robust systems?
How do you approach designing systems that need to scale across large codebases or enterprise environments?
Give an example of when you had to work across multiple teams (research, product, infrastructure) with conflicting priorities. How did you navigate it?
What excites you about AI and security, and how do those interests shape the kind of problems you want to solve?

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