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Prime Intellect is building an open frontier AI platform. This generalist software engineering role focuses on the developer-facing surface, APIs, and services used to train and deploy frontier models. You will own features end-to-end and ship at the pace of an early-stage startup.
You'll work on intuitive web interfaces, REST APIs, and cloud-based deployments, with an emphasis on production ownership, shipping quality code, and collaboration with researchers and engineers worldwide.
Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.
Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.
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
Modern frontend development (TypeScript, React/Next.js, Tailwind)
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
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.