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.
About Nominal
🚀 About The Role
✅ What You'll Do
⚡️ Skills That Accelerate Us
👀 Nice to Have
✨ Benefits/Perks
Nominal is building the connected test and operations platform powering the world's most advanced hardware systems, from spacecraft and autonomous vehicles to next-generation defense programs. Our platform gives hardware engineering teams a single place to ingest data, analyze performance, automate test execution, and collaborate across every phase of development, so they can move faster without sacrificing safety or precision. We're a fast-moving team that owns problems end-to-end, works across disciplines, and thrives at the intersection of hardware and software.
We serve top-tier commercial and defense customers, from autonomy leaders like Anduril and Shield AI to next-generation aerospace teams like Hermeus and REGENT, and performance engineering teams like Pratt Miller Motorsports, alongside mission partners within the U.S. Navy and U.S. Air Force on programs where failure isn’t an option. We’re backed by Sequoia, General Catalyst, Founders Fund, Lux Capital, and Lightspeed. Our team draws from SpaceX, Palantir, Anduril, Applied Intuition, and other leading companies, united by a common mission: giving hardware engineers the tools to build the future with speed, safety, and confidence.
We're building AI systems that reason over real-world engineering data to help engineers understand failures, investigate root causes, and accelerate mission-critical work. This is an opportunity to help define an entirely new category of software at the intersection of AI, distributed systems, and physical engineering.
We're looking for an experienced software engineer to join our Hardware Intelligence team. This is a highly ambiguous, zero-to-one engineering role. You'll build the infrastructure, data systems, and AI capabilities that power the next generation of intelligent engineering tools. Rather than implementing predefined product requirements, you'll work alongside customers and product leaders to discover what should exist, and then build it.
Success in this role comes from being comfortable making technical bets, rapidly prototyping new ideas, and turning uncertainty into working software.
- Build the systems that power Hardware Intelligence, including agent infrastructure, evaluation pipelines, retrieval systems, and tooling for reasoning over engineering data.
- Design and ship AI-powered workflows that help engineers investigate anomalies, perform root cause analysis, and understand complex hardware behavior.
- Work across large-scale time series, telemetry, logs, and other engineering datasets to build robust, production-ready systems.
- Prototype new approaches quickly, evaluate them with customers, and iterate based on real-world feedback.
- Partner closely with engineers and product leaders to determine where the team should invest next.
- Help establish engineering patterns, infrastructure, and best practices as Hardware Intelligence scales.
- Engage directly with customers to understand how complex engineering problems are solved today and translate those workflows into product capabilities.
We're less interested in checking every technical box than finding someone who thrives in early-stage environments and enjoys solving difficult, undefined problems.
You might be a great fit if you have:
- 5+ years of experience building AI or machine learning products that shipped to production.
- Experience working with large datasets, time series data, observability platforms, data infrastructure, or machine learning systems.
- A background in ML, data science, applied AI, or adjacent fields that gives you strong intuition for working with data-intensive systems.
- Strong software engineering fundamentals, with experience designing scalable backend or distributed systems.
- Experience taking products from zero-to-one, whether at a startup or inside an entrepreneurial team within a larger company.
- Strong product instincts and curiosity about customer problems.
- Experience working with telemetry, sensors, robotics, aerospace, industrial systems, autonomous systems, or other hardware domains.
- Experience building agentic systems, LLM applications, retrieval pipelines, or evaluation infrastructure.
- Familiarity with time series databases, observability tooling, or data platforms.
- Experience supporting engineers or scientists working with large-scale operational data.
- Prior startup founding experience or experience on an incubation/new products team.
- 🏥 100% coverage of medical, dental, and vision insurance
- 🏖️ Unlimited PTO and sick leave
- 🍽️ Free lunch, snacks, and coffee
- 🚀 Professional Development Stipend
- ✈️ Annual company retreat
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.
ITAR Requirements
To conform to U.S. Government export regulations, applicant must be a (i) U.S. citizen or national, (ii) U.S. lawful, permanent resident (aka green card holder), (iii) Refugee under 8 U.S.C. § 1157, or (iv) Asylee under 8 U.S.C. § 1158, or be eligible to obtain the required authorizations from the U.S. Department of State. Learn more about the ITAR here.
Similar Jobs
Healthtech
Build and operate scalable AI platform infrastructure enabling secure, reliable access to foundation models and AI agents. Responsibilities include developing model gateways, provider integrations, routing, usage controls, observability, governance, and self-service platform capabilities. The role involves architecting distributed systems, improving reliability and security, collaborating across engineering and product teams, mentoring engineers, and establishing high-quality engineering practices.
Top Skills:
AlertingAPIsAWSAws BedrockAzureAzure OpenaiC#C++Ci/CdContainersDashboardsDistributed TracingGCPGoGoogle Vertex AiIdentity And Access ControlInfrastructure As CodeJavaKubernetesLoggingMetricsPythonScalaSecrets ManagementSlosSQL
Cloud • Information Technology • Cybersecurity • Infrastructure as a Service (IaaS)
Lead development of a unified fleet knowledge model and decision-capture pipeline for autonomous data-center operations. Build data access layers across relational, telemetry, monitoring, and time-series systems; capture labeled operator decisions; negotiate data requirements with source-system owners; and own scaling considerations including vector indexing, schema evolution, retention, and analytics separation. The role requires strong infrastructure-domain modeling, PostgreSQL expertise, and experience handling time-series and event data at scale.
Top Skills:
DcgmDcimPostgresSlurmTime-Series DataVector Search
Mobile • Security • Software • Cybersecurity
Build full-stack software, backend services, APIs, frontend experiences, and shared integration capabilities supporting AI initiatives across Keeper’s products. Integrate LLMs, agents, and tool-calling workflows into secure production environments while maintaining zero-knowledge principles. Troubleshoot cross-product systems, improve reliability and observability, contribute to architecture and code reviews, automate testing and CI/CD, and collaborate with AI, product, and engineering teams.
Top Skills:
Ai AgentsAWSC#ChatgptCi/CdClaudeEvent-Driven ArchitectureGitGithub CopilotGoJavaJavaScriptKotlinLinuxLlm ApisMicroservicesModel Context Protocol (Mcp)PythonReactRustTypescriptWindows
What you need to know about the Seattle Tech Scene
Home to tech titans like Microsoft and Amazon, Seattle punches far above its weight in innovation. But its surrounding mountains, sprinkled with world-famous hiking trails and climbing routes, make the city a destination for outdoorsy types as well. Established as a logging town before shifting to shipbuilding and logistics, the Emerald City is now known for its contributions to aerospace, software, biotech and cloud computing. And its status as a thriving tech ecosystem is attracting out-of-town companies looking to establish new tech and engineering hubs.
Key Facts About Seattle Tech
- Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Amazon, Microsoft, Meta, Google
- Key Industries: Artificial intelligence, cloud computing, software, biotechnology, game development
- Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Madrona, Fuse, Tola, Maveron
- Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute
