OpenAI
AI Frontier · AI lab
- HQ
- San Francisco, US
- Founded
- 2015
- Size
- 5,000+
- Website
- openai.com
- Blog
- openai.com
Products
Currently tracking 199 active AI roles, down 29% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $230k–$555k (avg $372k).
AI Frontier · AI lab
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 |
|---|---|---|
| Researcher, Training - London Researcher focused on pushing the frontier of LLM development, enhancing intelligence, efficiency, and adding new capabilities through research into architecture design, long-context, efficient attention, optimization, and scaling. The role involves designing, prototyping, and scaling new architectures, executing and analyzing experiments, optimizing model and computational performance, and contributing to training and inference infrastructure. Experience with major LLM training runs and evaluating deep learning architectures is desired. | Pretrain | 10 |
| Manager, AI Deployment Engineering - Codex Manager for AI Deployment Engineering focused on the Codex product, responsible for leading a team that helps customers integrate and scale AI coding tools into their software development lifecycle. The role involves technical leadership, customer engagement strategy, and partnering with product and research teams to drive adoption and gather feedback. |
| Ship |
| 9 |
| 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 |
| Manager, Forward Deployed Engineering - London Manager for Forward Deployed Engineering team responsible for partnering with customers to turn research breakthroughs into production systems, owning end-to-end delivery outcomes, and informing roadmap priorities through fieldwork. Requires experience managing customer-facing engineers and leading high-pressure technical projects. | Ship | 9 |
| Training, Process Management Engineer OpenAI's Training Runtime team is seeking a Process Management Engineer to build and maintain the distributed OS responsible for launching, coordinating, and supervising large-scale machine learning training workloads. This role involves working with Rust and Python to create high-performance, reliable, and observable systems that enable researchers to scale ideas from experiments to production training runs on massive clusters. | Data | 8 |
| Software Engineer, Platform Systems Software Engineer on the Platform Systems team at OpenAI, responsible for designing and building distributed systems for failure detection, tracing, and observability to support large-scale AI model training. The role focuses on improving the reliability, performance, and visibility of OpenAI's training infrastructure. | Data | 8 |
| 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 |
| AI Deployment Engineer, Large Enterprise AI Deployment Engineer role focused on post-sale customer engagement to ensure safe and effective deployment of Generative AI applications for developers and enterprises. The role involves acting as a trusted advisor, helping customers build and execute AI adoption strategies, identify and prioritize GenAI use cases, and guide projects from prototype to production. Responsibilities include serving as a technical subject matter expert, engaging with senior stakeholders, providing architectural guidance, building prototypes, and contributing to knowledge sharing. | Ship | 7 |
| 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 |
| Data Scientist, Integrity Measurement Data Scientist focused on measuring and responding to adversarial threats and misuse on OpenAI's platforms, developing AI-first methods for prevalence estimation and productionised safety metrics, and optimizing LLM prompts for measurement. This role involves owning measurement and metrics for severe harm verticals, informing improvements to detection and enforcement, and leveraging agentic products for automation. | Eval Gate | 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 |
| Software Engineer, Codex Ecosystem & Enterprise Software Engineer focused on building the ecosystem, enterprise capabilities, and product experiences for Codex, an AI software engineer. This role involves working across the full stack to enable deployment, operation, and trust of Codex in demanding real-world environments, including integrating with enterprise identity and governance systems, and leading customer deployments. | ShipAgent | 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 |