# Principal Software Engineer, Codex Cyber

**Company:** [OpenAI](https://hotfix.jobs/companies/openai)
**Location:** San Francisco, CA
**Role:** ML Engineering
**Salary:** $347k – $490k/yr
**Experience:** 10+ years
**Skills:** Python, TypeScript, JavaScript, Ml Systems, Cyber Evaluations, Model Training, Safety Engineering, Security Products
**Posted:** 2026-07-09

> Principal engineer on OpenAI's Codex Cyber team building AI-powered security products for trusted defenders. Define roadmaps, shape model training and safeguards, build evaluations for cyber capabilities and risks, and translate frontier research into production tools while collaborating across product, research, safety, and external partners.

## Job Description

## Responsibilities
- Define and execute the technical roadmap for Codex Cyber’s security products, including evaluations, safeguards, trusted-defender workflows, and deployment decisions.
- Work with trusted defenders, customers, and partner teams to understand cyber use cases, evaluate risk, and turn feedback into product and research priorities.
- Shape cyber-specific model training and access patterns, including data, evaluations, validation, and deployment criteria.
- Build and validate systems for measuring cyber capabilities, monitoring misuse risk, and proving safeguards work in practice.
- Collaborate with Safety/Preparedness, Research, Security, Legal, Communications, Go-to-Market, and external partners on company-wide cyber priorities.
- Translate frontier cyber research into launch-ready tools, operational playbooks, and durable infrastructure for Codex and security products.

## Requirements
- 10+ years of experience in Python, TypeScript/JavaScript, or similar languages, with the judgment to build reliable systems in ambiguous, high-stakes domains.
- Experience in ML systems, security products, cyber evaluations, model training, safety engineering, or trusted customer deployments.
- Ability to think clearly about cyber capability, misuse risk, access patterns, safeguards, and deployment tradeoffs in high-stakes environments.
- Enjoy 0 -> 1 environments, can navigate ambiguity, and are excited to build security products that bring frontier AI capabilities to trusted defenders responsibly.
- Can move fluidly between product launches, customer and defender partnerships, model training, evaluation science, and security research.

## Nice-to-Haves
- Background in ML systems, security products, cyber evaluations, model training, safety engineering, or trusted customer deployments.

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