Senior Systems Engineer, Enterprise AI Platforms

Role details

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: IT Engineering at CoreWeave designs, builds, and operates the systems that enable our employees and acquired organizations to work securely and efficiently at scale. The team partners closely with Security, Business Development, PeopleOps, and Corporate functions to deliver resilient, standardized, and automation-first IT solutions that support CoreWeave's rapid growth. About the role: CoreWeave is hiring a Senior AI Platform Engineer to own the design, implementation, and governance of AI across CoreWeave's employee environment. You'll be the technical owner for the AI tools our employees use every day, on every surface they ship on: chat assistants, desktop apps, coding agents, AI terminals, AI browsers, workplace knowledge tools, and whatever comes next. You'll make them safe to adopt by building CoreWeave's guardrails directly into the platform through identity, device, and tenant-level controls rather than policy documents alone. This role is for someone who is genuinely passionate about AI and lives on its bleeding edge: someone who is already tuning agent behavior every week, has run swarms of agents and agent loops rather than just chatted with a model, and wants to keep learning at the velocity this field now moves. The tools, models, and best practices in this job will change monthly. That should excite you, not exhaust you. This is not a traditional AI/ML engineering role, and it is not a traditional IT administration role. It is deliberately a composite role that combines three things: production software and SRE engineering, hands-on LLM and agent work, and enterprise IT controls across identity, devices, and SaaS. We expect strong candidates to arrive deep in two of the three and grow into the third. Tell us which two. What success looks like in the first year: CoreWeave employees get frontier AI capabilities before almost any enterprise on earth. When a vendor ships a new model, agent surface, or feature, you already know it's coming; you're plugged into vendor roadmaps, betas, and the community and you have an evaluated, governed rollout ready in days, not quarters. That speed is possible because of the foundation you build in year one: sanctioned tools governed through identity, a connector and MCP allowlist in production, an intake process so "is this allowed" has an answer, internal agents shipping through an IT-owned gateway, and leadership visibility into usage, cost, and risk. The foundation is the floor; the pace is the job. AI platform lifecycle and governance Own the end-to-end lifecycle of employee-facing AI platforms across every surface they ship on (web, desktop, mobile, IDE, terminal, and browser): evaluation, procurement support, tenant design, rollout, configuration management, and ongoing operations. Keep the Platforms in Scope list current as the market moves. Establish CoreWeave's AI operating framework for IT: intake and review for new AI tools and agents, standards for internal bots, runbooks, a clear path from pilot to supported service, and enablement content that helps employees use AI tools well and safely. Guardrails as enforceable controls Design and implement AI guardrails as enforceable controls, in partnership with Enterprise Security and IT Identity and Access: SSO and SCIM provisioning, role- and group-based feature entitlement, data-retention and training opt-out settings, browser-extension and desktop-app policy, and device-trust requirements for access. Build and operate connector and MCP allowlists with data-source scoping across Okta, Google Workspace, Slack, Atlassian, GitHub, ITSM, and HRIS. Partner with Enterprise Security, Legal, and Privacy to translate acceptable-use, data-classification, and regulatory requirements into technical policy, and support audits with the evidence those controls produce. Infrastructure you'll own The IT-owned control layer for CoreWeave's internal chatbots and agents: the gateway, identity, secrets, MCP allowlisting, logging, rate limiting, and cost attribution in front of the serving stack, deployed on CoreWeave infrastructure alongside the teams that run it. Inference endpoints, agent hosts, and developer AI tooling on managed devices, treated as managed endpoints with a lifecycle, configuration baselines, and observability. The IT-owned share of CoreWeave's internal MCP servers, reusable agent skills, and shared agent configuration (system prompts, AGENTS.md and CLAUDE.md instruction files, tool policies), plus the identity, logging, and allowlisting standards, with reference implementations, that agents and MCP servers built by other teams must meet. Operations, reliability, and telemetry Hold the AI services you own to SRE standards: automation and infrastructure-as-code for everything repeatable, reliability targets, on-call, and incident response. Instrument usage, cost, quality, and risk telemetry across AI platforms, and build the dashboards and alerting that show leadership what is being used, by whom, and at what spend. Serve as the senior escalation point for AI tooling issues. Communicate clearly and proactively with executives, cross-functional partners, and employees. Who You Are: 6+ years in software engineering, site reliability engineering, or IT systems engineering where you built and ran things in code, not just configured them. 2+ years of hands-on experience building with or administering LLM-based products: API integration, prompt and tool de