Senior Systems Engineer, Enterprise AI Platforms
CoreWeave · Sunnyvale, CA / Bellevue, WA
About this role
**CoreWeave — Senior Systems Engineer, Enterprise AI Platforms** ## What you’ll do IT Engineering at CoreWeave designs, builds, and operates the systems that help employees and acquired organizations work securely and efficiently at scale. You’ll partner closely with Security, Business Development, PeopleOps, and Corporate functions to deliver resilient, standardized, automation-first IT solutions. CoreWeave is hiring a **Senior AI Platform Engineer** to own the design, implementation, and governance of AI across the employee environment. You’ll be the technical owner for the AI tools employees use daily across every surface they ship on—**chat assistants, desktop apps, coding agents, AI terminals, AI browsers, workplace knowledge tools, and more**. You’ll make these tools safe to adopt by building **guardrails directly into the platform** using **identity, device, and tenant-level controls** (not just policy documents). This is a composite role combining: - **Production software + SRE engineering** - **Hands-on LLM + agent work** - **Enterprise IT controls** across identity, devices, and SaaS ## Success in your first year Employees get frontier AI capabilities quickly—when vendors ship new models/features, you’ll have an evaluated, governed rollout ready in **days, not quarters**. You’ll establish the foundation: sanctioned tools governed through identity, connector/MCP allowlists in production, an intake process for “is this allowed?”, internal agents shipping through an IT-owned gateway, and leadership visibility into usage, cost, and risk. ## Key responsibilities ### AI platform lifecycle & governance - Own the end-to-end lifecycle of employee-facing AI platforms across web, desktop, mobile, IDE, terminal, and browser: **evaluation, procurement support, tenant design, rollout, configuration management, and operations**. - Keep the **Platforms in Scope** list current. - Establish CoreWeave’s **AI operating framework** for IT: intake/review for new tools/agents, standards for internal bots, runbooks, a clear pilot-to-supported-service path, and enablement content for safe usage. ### Guardrails as enforceable controls - Design and implement AI guardrails with Enterprise Security and IT Identity & Access, including: - **SSO + SCIM provisioning** - Role/group-based feature entitlement - Data-retention and training opt-out settings - Browser-extension and desktop-app policy - Device-trust requirements - 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 control evidence. ### Infrastructure you’ll own - The IT-owned control layer for internal chatbots/agents: gateway, identity, secrets, MCP allowlisting, logging, rate limiting, and cost attribution in front of the serving stack. - Inference endpoints, agent hosts, and developer AI tooling on managed devices (lifecycle, baselines, observability). - The IT-owned share of internal MCP servers, reusable agent skills, shared agent configuration (e.g., system prompts and instruction files like **AGENTS.md / CLAUDE.md**), plus identity/logging/allowlisting standards and reference implementations. ### Operations, reliability, and telemetry - Hold AI services to **SRE standards**: automation and infrastruct
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