Nominal
Software Engineer - Full-Stack
New York, USA
Sponsorship not specifiedDetected 252 days ago
TypeScriptJavaGoReactNext.jsCSSTailwind CSSNode.jsDistributed SystemsFull-Stack DevelopmentGraphQLRESTData VisualizationHardware DesignCollaboration
About the role
- Develop end-to-end functionality using modern frameworks like React, Next.js, TypeScript, and Node.js
Responsibilities
- We're a fast-moving team that owns problems end-to-end, works across disciplines, and thrives at the intersection of hardware and software.
- Optimize both frontend and backend performance to deliver fast, seamless user experiences under heavy load.
- Work closely with product, design, and engineering teams to validate designs, integrate APIs such as tRPC, and deliver features that are both technically sound and user-centric.
- Skilled in building scalable distributed systems and integrating RESTful or GraphQL APIs.
Nice to have
- Familiarity with Tailwind CSS, Radix UI, data visualization tools, and WebGL experience is a plus.
Skills
- Experience in React, Next.js, and TypeScript, and/or backend experience in Java, Go, or Rust.
Company info
- About Nominal 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 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.
Visa & Work Authorization
- citizen or national, (ii) U
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This listing is sourced directly from Nominal's careers page and normalized into a canonical job model.