Jobs at Nominal

Embeds with hardware engineering teams to build agentic workflows and AI skills that perform engineering tasks, including requirements checks, test-plan analysis, and issue investigation. Demonstrates value to customers, identifies reusable patterns, and translates customer needs into product capabilities. Requires strong Python and data skills, customer-facing communication, modern AI coding-agent experience, and willingness to travel. Hardware, test, controls, forward-deployed, solutions engineering, and security-clearance experience are advantageous.

Design and build the platform powering Nominal’s AI agents, MCP, workflows, integrations, and customer-facing tools. Develop LLM features involving prompting, tool design, retrieval, observability, and evaluation. Collaborate directly with hardware engineers and customer programs, convert field insights into scalable capabilities, and own agent functionality from concept through production. The role also involves shaping technical direction and improving how agents support hardware testing and operations.

Lead development of AI agent products and AI-native applications for hardware engineering workflows. Prototype ideas rapidly, build products end to end, improve agent user experiences, establish interaction patterns, and lead technical direction across product engineering. Partner with design, product, and platform teams while working closely with engineers and users.

Design and build the platform powering Nominal’s AI agents, including orchestration, planning, tool calling, memory, background execution, retrieval, context assembly, model routing, and fallbacks. Set technical direction, establish architecture, collaborate on evaluations and platform growth, mentor engineers, and deliver reliable LLM and agent systems to production.

Build and rapidly prototype AI-native product features for hardware engineers. Develop full-stack interfaces, APIs, streaming agent workflows, citations, editable outputs, and trustworthy human-agent handoffs. Own product decisions from concept through customer delivery, observe real users, and iterate on usability. The role requires strong front-end development with TypeScript and React, experience with AI-powered interfaces, rapid prototyping, product ownership, and modern AI coding-agent workflows.

The Deployment Systems Engineer will deploy and monitor infrastructure for advanced hardware systems, manage projects, and innovate in air-gapped environments.

Build, optimize, and maintain large-scale build systems (Bazel), CI/CD pipelines, and release automation. Own developer infrastructure, observability, telemetry, logging, and metrics. Partner with product teams to remove developer friction and improve engineering productivity as the monorepo and organization scale.

Build scalable React/TypeScript frontends to visualize and interact with large-scale, real-time telemetry. Define data models and workflows, optimize rendering and performance, collaborate with product, design, and backend teams, and turn ambiguous requirements into intuitive, mission-critical interfaces for technical users.

Build infrastructure and AI systems for Hardware Intelligence: agent infrastructure, retrieval and evaluation pipelines, and tooling to reason over large-scale time series, telemetry, and engineering datasets. Prototype and ship AI-powered workflows for anomaly investigation and root cause analysis, work directly with customers, and establish engineering patterns as the platform scales.

As a Mission Operations Engineer, you will deploy and integrate solutions, build relationships with clients, provide training, enhance products, and solve operational issues.

Own deployment and operation of Nominal's self-hosted, air-gapped, and on-prem infrastructure. Troubleshoot Linux, networking, Kubernetes, and storage in production, work directly with customer IT and security teams, build provisioning automation, runbooks, and observability, and support critical onsite implementations while shaping strategy for regulated deployments.