Jobs at Nominal

Build AI-powered product experiences for hardware engineers. Prototype features rapidly, develop interfaces and APIs, stream agent workflows, make AI actions trustworthy with visible steps and citations, and own product decisions from concept through customer use. Collaborate closely with users, iterate based on feedback, and create polished full-stack applications involving generative interfaces, asynchronous jobs, rich data visualization, and real-time interactions.

Build and lead zero-to-one AI agent products for hardware engineers. Prototype agent interactions, shape products, develop and ship end-to-end applications, establish agent UX patterns, and transform hardware workflows into agent-native experiences. The role requires strong frontend and full-stack engineering, product judgment, user empathy, and technical leadership across product engineering teams.

Design, build, and operate distributed backend systems for ingesting, storing, querying, and processing high-frequency hardware telemetry and multimodal data. Responsibilities include storage and indexing design, scalability, fault tolerance, performance optimization, reliability improvements, and production operations. The role collaborates across product and infrastructure teams, influences architecture, mentors engineers, and owns systems end to end.

Graduate engineers will build software platforms, features, integrations, data pipelines, and applications for high-volume hardware data. They may work directly with customers in the field, own projects from discovery through deployment and support, iterate based on user feedback, and help expand Nominal’s London team. Applicants should be final-year students graduating in summer 2027 with strong engineering skills and practical experience from placements, internships, projects, hackathons, societies, or coursework.

Design and build the platform powering Nominal’s AI agents, MCP, and internal agent applications. Develop agent tools, workflows, integrations, and customer-facing capabilities for hardware engineering use cases. Instrument systems, evaluate performance, debug production issues, and collaborate directly with customer engineering teams. The role requires owning capabilities end to end, shipping iteratively, and applying hands-on experience with LLM features, prompting, retrieval, and tool design.

Embed with hardware engineering customers to build agentic workflows that perform real engineering tasks, including requirements checks, test-plan analysis, issue investigation, and reusable AI skills. Demonstrate measurable customer value, identify patterns for product development, and represent customer needs internally. The role requires strong Python and data skills, customer-facing communication, modern AI coding-agent experience, and travel to customer sites.

Design and build the platform powering Nominal’s AI agents, including orchestration, planning, tool calling, memory, retrieval, model routing, and autonomous background agents. Own the shared MCP tool layer, establish agent architecture and technical direction, improve evaluation and reliability, and mentor engineers. The role requires shipping production LLM or agent systems, strong distributed-systems and backend expertise, and working in-office five days per week.

As a Mission Operations Engineer, you'll deploy and integrate Nominal’s technology, enhance user experiences, provide training, and resolve operational challenges while building relationships with clients.

The Software Engineer on Mission Dev will build custom applications, design data pipelines, and collaborate closely with clients to solve complex challenges. Responsibilities include direct customer engagement and contributing to team growth.