Senior Production Engineer, Tooling & Frameworks

<div class="content-intro"><div> <div> <div class="gmail_quote"> <div> <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&nbsp;<a href="http://www.coreweave.com/" target="_blank" data-saferedirecturl="https://www.google.com/url?q=http://www.coreweave.com&amp;amp;source=gmail&amp;amp;ust=1762613132717000&amp;amp;usg=AOvVaw3D-UOhNaqEvF5BEWxjYyAU&quot;&gt;www.coreweave.com&lt;/a&gt;.&lt;/span&gt;&lt;/div> </div> </div> </div> </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> <ul> <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> </ul> <h3><span style="font-size: 10pt;"><strong>What You’ve Worked On (Minimum Qualifications)</strong></span></h3> <ul> <li style="font-size: 10pt;"><span style="font-size: 10pt;">5+ years in software or infrastructure engineering building and operating distributed systems at scale.</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Proficiency in Python (or similar), with experience delivering production microservices and data pipelines.</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Expertise in Kubernetes, container orchestration, and cloud-native architectures.</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Strong understanding of data systems (streaming, indexing, caching, ETL).</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Demonstrated experience designing for scalability, fault tolerance, and performance.</span></li> </ul> <h3><span style="font-size: 10pt;"><strong>Preferred Qualifications</strong></span></h3> <ul> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Experience building RAG systems or embedding-based search.</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Familiarity with vector databases and text/signal retrieval systems.</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Experience developing or deploying agentic AI systems (LLM-based automation, AI observability).</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Strong distributed-systems background (consensus, message buses, job orchestration, eventual consistency).</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Experience designing data schemas and APIs for knowledge representation and operational reasoning.</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Familiarity with ChatOps frameworks or workflow orchestration (Temporal, Argo, Airflow).</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Background in MLOps, AI infrastructure, or platform reliability engineering.</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Experience with observability frameworks (Prometheus, Grafana, OpenTelemetry) and using telemetry for automated reasoning or remediation.</span></li> </ul> <h3><span style="font-size: 10pt;"><strong>Why CoreWeave</strong></span></h3> <p><span style="font-size: 10pt;">At CoreWeave, we work hard, have fun, and move fast. You’ll join a team that values curiosity, ownership, and creative problem-solving. As part of Production Engineering, you’ll operate at the intersection of AI and reliability — building systems that make operating the most powerful AI cloud in the world smarter every day.</span></p> <p><span style="font-size: 10pt;"><strong>Core Values:</strong></span></p> <ul> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Be Curious at Your Core</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Act Like an Owner</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Empower Employees</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Deliver Best-in-Class Client Experiences</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Achieve More Together</span></li> </ul> <p>The base salary range for this role is $139,000 to $204,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).&nbsp;</p><div class="content-conclusion"><p><strong>What We Offer</strong></p> <p>The range we’ve posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location.</p> <p>In addition to a competitive salary, we offer a variety of benefits to support your needs, including:</p> <ul> <li>