Key Responsibilities
- Product surfaces people touch every day across Hermes Agent and Nous Portal, on web, desktop, and mobile.
- Backend services and APIs that hold up under real usage.
- The cloud platform and infrastructure behind our products and model serving.
- Developer and research tooling that makes the rest of the team faster.
- Whatever the highest-leverage problem is that quarter, which is not always predictable at a company moving this fast.
Qualifications & Requirements
- 3+ years building and shipping production software that real people depend on.
- Depth in at least one area (frontend, backend, infrastructure, systems, or ML tooling) and the range to work outside it.
- Fluency in the languages we use day to day, mainly TypeScript and Python, and comfort reaching for a systems language like Rust when it's the right call.
- Strong ownership: you see something broken or missing and you fix it without waiting to be asked.
- Heavy use of AI-assisted development in your own workflow.
- Clear communication and low ego, because the team is small and everyone reads each other's code.
Preferred
- Experience with AI products, LLM applications, agents, or tool-calling workflows.
- Open-source contributions, or side projects you're proud enough to show us.
- Familiarity with modern AI infrastructure: PyTorch, OpenAI-compatible APIs, model routing, or inference.
About Nous Research
Nous Research, founded in 2023 by a distributed collective of AI researchers and open-source contributors, builds decentralized AI models and training infrastructure for open, aligned intelligence. Its work includes open-weight Hermes models, Psyche decentralized training that coordinates global GPU contributions, and inference tooling that lets developers run models without centralized APIs. Headquartered with a fully distributed team across North America and Europe, Nous emphasizes open research, model evaluation and community-driven alignment over proprietary development. The project collaborates with open-source communities and crypto incentive designers to fund compute and data contributions transparently. Its collective publishes evaluations, datasets and training playbooks that let open-source contributors reproduce, fine-tune and deploy models with transparent provenance. Expect a research and community-driven culture that values model openness, rigorous evaluation and empowering builders to deploy capable AI without reliance on closed providers.