> Markdown version of [/jobs/ext/3241646-principal-software-engineer-models](https://www.wearedevelopers.com/jobs/ext/3241646-principal-software-engineer-models). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Software Engineer - Models - **Company:** Coreweave Inc - **Location:** New York, NY, United States - **Experience:** Expert - **Salary:** $227,000.0 - $303,000.0 - **Contract:** Permanent contract - **Skills:** TypeScript, Datadog, ReactJS, Backend, Graphql, Machine Learning Operations, Front End Software Development, React Redux, Virtual Agents, Api Design - **Published:** September 17, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=80dbc4b925e49e97 ## About the Role * 8+ years building user-facing software, with deep expertise in frontend architecture and performance * Have led the transformation of a large, long-lived React application with a focus on performance, product impact and dev experience and owned the outcome * Strong command of React and TypeScript, with production experience in GraphQL and a modern state management approach such as Redux or Zustand, including opinions on when each is the right tool * Real performance engineering skill: you can instrument an application, read both frontend and backend traces, determine precisely where time is going, and prove the improvement with numbers * Solid client-side caching fundamentals, including normalization, invalidation, and the failure modes that appear at scale * Hands-on experience with bundlers and build tooling, and clear views on code splitting and delivery tradeoffs * Enough backend depth to design systems at a high level. You can propose a new API architecture in service of a faster client and reason about its frontend implications * Track record of validating ideas, coordinating across engineering teams, and sequencing work that spans organizational boundaries * An operator mindset: you measure, you ship, you follow through, and you stay close to production, * Experience introducing automated enforcement such as lint rules, CI gates, or performance budgets that changed engineering behavior broadly * Background in data-dense or visualization-heavy applications where rendering cost and data volume are the core constraints * Familiarity with observability tooling such as Datadog RUM and APM, or comparable tracing and session-replay stacks * Working knowledge of Go or a similar backend language * Exposure to ML, MLOps, or AI agent workflows, or genuine curiosity about the researchers and engineers who use these tools * Experience with a highly configurable product, where the space of user and deployment settings can't be exhaustively tested