OpenAI
AI Frontier · AI lab
- HQ
- San Francisco, US
- Founded
- 2015
- Size
- 5,000+
- Website
- openai.com
- Blog
- openai.com
Products
AI Frontier · AI lab
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 |
|---|---|---|
| Forward Deployed Engineer - Dublin This role focuses on leading end-to-end deployments of frontier AI models for strategic customers, involving technical scoping, system design, build, and production rollout. The engineer will partner closely with customer teams, contribute code, and codify working patterns into reusable tools. Success is measured by production adoption, workflow impact, and feedback that influences product and model roadmaps. The role requires experience in building or deploying LLM-powered systems and delivering complex systems in ambiguous environments. | AgentServe | 9 |