Jobs at NorthMist

Build and deploy agentic AI workflows for hardware engineering customers, including requirement checks, test-plan analysis, issue investigation, and reusable AI skills. Embed onsite with partner teams, demonstrate measurable value, identify reusable product patterns, and represent customer needs internally. The role requires strong Python and data skills, hands-on agentic workflow experience, customer-facing communication, travel, and familiarity with modern AI coding agents. Hardware engineering, forward deployment, solutions engineering, productization, and security clearance experience are preferred.

Design and build Nominal’s AI agent platform, tools, workflows, MCP integrations, and internal agent capabilities. Ship LLM features for hardware engineering customers, instrument products, analyze traces and evaluations, and improve agent performance based on user feedback. The role requires close collaboration with customer engineers and ownership from concept through production.

Build and lead zero-to-one AI agent products for hardware engineering workflows. Prototype agent interactions, develop products end to end, improve agent user experience, establish interaction patterns, and transform hardware reviews, qualification, and reporting into agent-native applications. Lead product engineering direction and collaborate with design, product, and platform teams.

Build and rapidly prototype AI-native product features for hardware engineers. Develop interfaces, APIs, streaming agent workflows, citations, and editable handoffs. Own product decisions, validate ideas with users, and iterate toward polished experiences. The role requires strong full-stack and frontend skills, TypeScript and React experience, AI interface development, product ownership, and familiarity with modern AI coding agents.

Design and build Nominal’s agent platform, including orchestration, planning, tool calling, memory, background execution, context retrieval, model routing, and reliability features. Establish architecture for agents and MCP, partner on evaluation and platform strategy, and provide technical leadership through design reviews and mentorship. The role requires production experience with LLM or agent systems, strong distributed-systems fundamentals, and the ability to set technical direction.