Senior Production Engineer, Tooling & Frameworks
CoreWeaveLivingston, NJ / New York, NY / Sunnyvale, CA / Bellevue, WA$139k – $204kPosted 24 February 2026
Job Description
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<div><span id="m_1770241969069985273m_-2746164444908759431gmail-docs-internal-guid-131e4fb0-7fff-b4e9-ff50-e8cf32449b1b">CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at <a href="http://www.coreweave.com/" target="_blank" data-saferedirecturl="https://www.google.com/url?q=http://www.coreweave.comsource=gmailust=1762613132717000usg=AOvVaw3D-UOhNaqEvF5BEWxjYyAU">www.coreweave.com</a>.</span></div>
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</div></div><h3><span style="font-size: 10pt;"><strong>About the Role</strong></span></h3>
<p><span style="font-size: 10pt;">Production Engineering ensures CoreWeave’s cloud runs with world-class reliability, performance, and operational excellence. Herd is our newest innovation: an agentic AI platform that serves as CoreWeave’s intelligent SRE assistant - combining AI reasoning, data infrastructure, and observability into an autonomous operational intelligence layer for internal use.</span></p>
<p><span style="font-size: 10pt;">As a Production Engineer on Herd, you’ll define and build the systems that power a scalable agentic ecosystem. You’ll design distributed services and data pipelines that process, embed, and retrieve operational knowledge at scale, enabling LLM-powered agents to work alongside human engineers in production. This is a hands-on role at the intersection of AI operations, distributed systems, and data infrastructure.</span></p>
<h3><span style="font-size: 10pt;"><strong>What You’ll Do</strong></span></h3>
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<li style="font-size: 10pt;"><span style="font-size: 10pt;">Architect and build large-scale distributed systems that power AI SRE Platforms.</span></li>
<li style="font-size: 10pt;"><span style="font-size: 10pt;">Design data infrastructure for AI reasoning (embedding generation, context retrieval, vector stores) optimized for real-time operational queries.</span></li>
<li style="font-size: 10pt;"><span style="font-size: 10pt;">Build agent orchestration and lifecycle components so agents can communicate, delegate, and reason collectively across CoreWeave systems.</span></li>
<li style="font-size: 10pt;"><span style="font-size: 10pt;">Integrate AI SRE Platform with a large number of internal systems (Kubernetes, observability platforms, etc.) to enable end-to-end automation and insights.</span></li>
<li style="font-size: 10pt;"><span style="font-size: 10pt;">Lead architectural design discussions and set technical direction for AI-driven reliability systems.</span></li>
<li style="font-size: 10pt;"><span style="font-size: 10pt;">Partner across Production Engineering, Data Engineering, ML Infrastructure, and Platform to operate AI SRE as a high-availability platform embedded in critical reliability workflows.</span></li>
<li style="font-size: 10pt;"><span style="font-size: 10pt;">Develop services that interpret telemetry, detect anomalies, and generate RCA (root cause analysis) and PIR (post-incident review) artifacts; trigger automated mitigations where appropriate.</span></li>
<li style="font-size: 10pt;"><span style="font-size: 10pt;">Codify operational best practices into services, APIs, and Kubernetes-native components.</span></li>
<li style="font-size: 10pt;"><span style="font-size: 10pt;">Participate in an on-call rotation supporting the systems you build.</span><br><br></li>
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<h3><span style="font-size: 10pt;"><strong>What You’ve Worked On (Minimum Qualifications)</strong></span></h3>
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<li style="font-size: 10pt;"><span style="font-size: 10pt;">5+ years ... (truncated, view full listing at source)
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