

Prime Intellect is building the open superintelligence stack - from frontier agentic models to the infrastructure that enables anyone to create, train, and deploy them. We aggregate and orchestrate global compute into a single control plane and pair it with the full RL post-training stack, and we build the developer platform that makes all of it usable.
We enable researchers, startups, and enterprises to run end-to-end reinforcement learning at frontier scale, adapting models to real tools, workflows, and deployment contexts.
We recently raised $15mm in funding (total of $20mm raised) led by Founders Fund, with participation from Menlo Ventures and prominent angels including Andrej Karpathy (Eureka AI, Tesla, OpenAI), Tri Dao (Chief Scientific Officer of Together AI), Dylan Patel (SemiAnalysis), Clem Delangue (Huggingface), Emad Mostaque (Stability AI), and many others.
This is a generalist software engineering role focused on building the product surface of Prime Intellect - the developer-facing platform, APIs, and services that researchers and engineers around the world use to train and deploy frontier models. You'll own features end-to-end, from design through deployment and monitoring, and ship at the pace of an early-stage company tackling one of the most important problems in AI.
Build intuitive web interfaces for AI workload management and monitoring
Develop REST APIs and backend services in Python
Own features end-to-end, from design through deployment and operation
Create real-time monitoring and debugging tools for users of the platform
Implement user-facing features for resource management and job control
Deploy and operate services on cloud infrastructure
Contribute to internal tooling, automation, and developer experience improvements
Strong Python backend development (FastAPI, async)
Modern frontend development (TypeScript, React/Next.js, Tailwind)
Experience building developer tools, dashboards, or platform products
RESTful API design and implementation
Comfortable working with cloud platforms (GCP a plus) and containerized deployments
A bias toward shipping, ownership of production code, and pragmatic engineering judgment
Infrastructure automation experience (Ansible, Terraform, Kubernetes)
Interest in or exposure to ML/AI workloads
WebSocket / real-time systems experience
Open-source contributions
Observability tooling (Prometheus, Grafana)
Prior experience at an early-stage startup
Cash compensation range of $150–300k with significant equity incentives
Flexible work arrangement (remote or San Francisco office)
Full visa sponsorship and relocation support
Professional development budget for courses and conferences
Regular team off-sites and conference attendance
Opportunity to shape the future of open AI development
You'll join a team of experienced engineers and researchers working on cutting-edge problems in AI infrastructure. We believe in open development and encourage team members to contribute to the broader AI community through research and open-source contributions.
We value potential over perfection - if you're a strong generalist engineer who is passionate about democratizing AI development, we want to talk to you.
Ready to help shape the future of AI? Apply now and join us in our mission to make powerful AI models accessible to everyone.