Job description

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 www.coreweave.com . What You'll Do: The Field Engineering organization at CoreWeave supports the clients running some of the largest AI workloads in the world. This team builds the tooling that engineers rely on to identify and diagnose customer issues faster. We work where AI and deterministic based systems meet live production infrastructure, so what we build has to be accurate, has to show its reasoning, and has to earn the trust of engineers who are the real experts solving issues. About the Role: As an AI Engineer, you'll design, build, and operate systems that engineers use during real customer incidents. You will define the right balance between deterministic and AI systems, and work with both. For AI systems, you'll own the agent logic, the retrieval behind it, the safeguards that stop it from acting on bad information, and the measurement that tells us whether it's actually helping. This is a full-ownership role: you ship your own services and stay responsible for how they behave in production. You'll work closely with the engineers who use what you build. In this role, you will: - Design and build AI agents that investigate and act on real customer issues. - Build the safeguards that make that safe: grounding model output in authoritative data, requiring human approval before consequential actions, and defining the conditions under which the system should stop. - Build and evaluate retrieval over a large body of historical support data, measured against how experienced engineers handled the same problems. - Determine the optimal balance between AI and deterministic logic. - Instrument these systems for quality, cost, and adoption, then use what you learn to decide what to build next. - Deploy and operate your own services on Kubernetes, including supporting them when something breaks. - Partner with support engineers and domain experts, including sitting in on live investigations to see where automation helps and where it gets in the way. Who You Are: - 3+ years of professional software engineering experience, with strong proficiency in Go or Python. - Experience taking an AI application from prototype to production use and supporting it afterward. - Hands-on experience with agent patterns: tool and function calling, multi-step orchestration, and handling incorrect model output. - Experience building and evaluating retrieval systems, including measuring quality against a baseline using held-out data. - Experience designing controls for automation that acts on production systems, such as approval steps, idempotency, and audit trails. - Experience diagnosing failures in LLM applications and fixing the underlying cause rather than the symptom. - Experience with observability for LLM applications, including tracing, cost, and latency. - Working knowledge of Kubernetes and experience deploying services through CI/CD. - Experience integrating with third party APIs, including authentication and secrets handling. Preferred: - Experience building conversational or chat-based interfaces for internal users. - A background in infrastructure, SRE, or technical support, and comfort reading logs and metrics from a live system. - Experience testing both deterministic and non-deterministic systems. - Experience with fine-tuning or building training datasets from production data. - Open source contributions to AI tooling or agent frameworks. Wondering if you're a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we've found compatible with our team. If some of this describes you, we'd love to talk. - You can tell the difference between the thing that's interesting and the thing that's urgent, and you'll say so out loud when they aren't the same. - You've worked with a team that already had tooling they liked, and found the integration instead of arguing for a rewrite. - You'd rather sit in on a real incident than infer how the work goes from a ticket. - Blunt feedback from the engineers using your software is the most useful thing you'll hear all week, and you don't get defensive about it. The base salary range for this role is $143,00 to $210,000. 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). What We Offer 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. In addition to a competitive salary, we offer a variety of benefits to support your needs. The benefits below reflect our US-based offerings for full-time employees; for roles in other locations, benefits vary and are shared during the hiring process. These include: Medical, dental, and vision insurance - 100% paid for by CoreWeave Company-paid Life Insurance Voluntary supplemental life insurance Short and long-term disability insurance Flexible Spending Account Health Savings Account Tuition Reimbursement Ability to Participate in Employee Stock Purchase Program (ESPP) Mental Wellness Benefits through Spring Health Family-Forming support provided by Carrot Paid Parental Leave Flexible, full-service childcare support with Kinside 401(k) with a generous employer match Flexible PTO Catered lunch each day in our office and data center locations A casual work environment A work culture focused on innovative disruption California Applicants California Consumer Privacy Act Equal Opportunity & Accommodations CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. As part of this commitment and consistent with the Americans with Disabilities Act (ADA) , CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: careers@coreweave.com . Export Control Compliance This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.

Requirements

Must-haves

Design and build AI agents that investigate and act on real customer issues.
Build the safeguards that make that safe: grounding model output in authoritative data, requiring human approval before consequential actions, and defining the conditions under which the system should stop.
Build and evaluate retrieval over a large body of historical support data, measured against how experienced engineers handled the same problems.
Determine the optimal balance between AI and deterministic logic.
Instrument these systems for quality, cost, and adoption, then use what you learn to decide what to build next.
Deploy and operate your own services on Kubernetes, including supporting them when something breaks.
Partner with support engineers and domain experts, including sitting in on live investigations to see where automation helps and where it gets in the way.
3+ years of professional software engineering experience, with strong proficiency in Go or Python.
Experience taking an AI application from prototype to production use and supporting it afterward.
Hands-on experience with agent patterns: tool and function calling, multi-step orchestration, and handling incorrect model output.
Experience building and evaluating retrieval systems, including measuring quality against a baseline using held-out data.
Experience designing controls for automation that acts on production systems, such as approval steps, idempotency, and audit trails.
Experience diagnosing failures in LLM applications and fixing the underlying cause rather than the symptom.
Experience with observability for LLM applications, including tracing, cost, and latency.
Working knowledge of Kubernetes and experience deploying services through CI/CD.

Nice-to-haves

Experience building conversational or chat-based interfaces for internal users.
A background in infrastructure, SRE, or technical support, and comfort reading logs and metrics from a live system.
Experience testing both deterministic and non-deterministic systems.
Experience with fine-tuning or building training datasets from production data.
Open source contributions to AI tooling or agent frameworks.
You can tell the difference between the thing that's interesting and the thing that's urgent, and you'll say so out loud when they aren't the same.
You've worked with a team that already had tooling they liked, and found the integration instead of arguing for a rewrite.
You'd rather sit in on a real incident than infer how the work goes from a ticket.
Blunt feedback from the engineers using your software is the most useful thing you'll hear all week, and you don't get defensive about it.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aikubernetesgopythonllmci/cd

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Pto

Parental Leave

Wellness