Currently tracking 199 active AI roles, down 29% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $230k–$555k (avg $372k).
OpenAI currently has 235 active AI-related job listings. The majority of these roles are in the application stage, accounting for 32% of the total, followed closely by the agents stage at 29%. The dominant function for hiring is Engineering, with 168 positions. Frequent tech tags include model_serving, evals, and agent_orchestration, suggesting a focus on deploying and managing AI models. In the last 30 days, OpenAI posted 50 new AI roles, representing a 14% increase compared to the previous 30-day period.
OpenAI currently has 254 active AI-related roles in our index. The most common open titles are: AI Deployment Engineer (4), Partner AI Deployment Engineer - AWS (4), AI Deployment Engineer - Startups (3), AI Deployment Engineer- Codex (3), AI Deployment Engineer, Startups (2). Most positions are in Engineering and Research.
OpenAI's active AI hiring is concentrated in: application (33%), agents (28%), serving infrastructure (10%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
OpenAI is hiring AI talent in: United States (203 roles), United Kingdom (14 roles), Japan (6 roles), Germany (5 roles).
Job postings at OpenAI most frequently reference: model serving, agent orchestration, evals, llm observability, inference infra.
In the past 30 days, OpenAI has posted 56 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| AI Deployment Engineer - Startups AI Deployment Engineer role focused on working with strategic startup customers to optimize AI systems, identify failure modes, and translate learnings into product improvements and evaluation systems. This role involves prototyping prompts and agents, designing evaluations, and acting as a technical partner to customers. | AgentEval Gate | 9 |
| Forward Deployed Engineer - London This role focuses on leading end-to-end deployments of frontier AI models for strategic customers, involving discovery, technical scoping, system design, build, and production rollout. The engineer will build full-stack systems, embed with customer teams, and contribute code when necessary, with success measured by production adoption, workflow impact, and feedback that influences product and model roadmaps. The role requires experience with LLMs or generative models and delivering complex systems in ambiguous environments. |
| Agent |
| 8 |
| Technical Threat Investigator, Threat Intel Engineering - UK This role involves investigating sophisticated threat actors targeting OpenAI's models and systems, building tooling and AI-assisted workflows to scale analysis, and translating findings into security improvements. The focus is on understanding adversary behavior, identifying misuse, and developing proactive defenses. | Agent | 7 |
| Software Engineer, Integrity Foundations - London Software Engineer role focused on building scaled foundational systems for detecting, tracking, and enforcing harm on OpenAI's platforms, leveraging advanced AI technologies to automate and augment these processes. The role involves collaboration with various experts and staying ahead of adversarial threats. | Agent | 7 |
| Product Manager, Integrity Product Manager for OpenAI's Integrity team, focusing on scaling product efforts and technical strategy to combat scaled abuse and novel misuse of AI services like ChatGPT, API, and Sora. Requires close collaboration with product, safety, policy, operations, and engineering teams to build tooling and infrastructure for detection and prevention of policy violations. | Agent | 7 |
| Protection Scientist Engineer, Intelligence and Investigations This role focuses on designing and building systems to proactively identify and enforce abuse on OpenAI's products, including developing abuse monitoring for new and existing products, and prototyping systems for detection, review, and enforcement. It involves investigating critical escalations and working cross-functionally with product, policy, and engineering teams. The role requires technical analysis, data engineering, and machine learning principles, with an emphasis on scaling and automating processes, particularly with language models. | Agent | 7 |