Senior Systems Engineer, Enterprise AI Platforms
$182k - $242k • Remote • Sunnyvale, CA / Bellevue, WA
Posted 5d ago
About the job
CoreWeave is seeking a Senior AI Platform Engineer to lead the design, implementation, and governance of AI tools for employees. This role involves owning the AI tools used daily across various platforms, ensuring their safe adoption through integrated identity, device, and tenant-level controls. The ideal candidate is passionate about AI's bleeding edge, enjoys rapid learning, and has a strong background in production software/SRE engineering, hands-on LLM/agent work, and enterprise IT controls. Success in the first year means enabling employees with frontier AI capabilities quickly and securely, establishing a robust AI operating framework, and building foundational controls for AI tool adoption.
Responsibilities
- Own the end-to-end lifecycle of employee-facing AI platforms, including evaluation, procurement support, tenant design, rollout, configuration management, and ongoing operations.
- Maintain an up-to-date list of in-scope AI platforms as the market evolves.
- Establish CoreWeave's AI operating framework for IT, covering intake and review processes for new AI tools and agents, standards for internal bots, runbooks, pilot-to-service transitions, and user enablement content.
- Design and implement AI guardrails as enforceable controls in partnership with Security and IT Identity and Access teams.
- Build and operate connector and MCP allowlists with data-source scoping across various enterprise tools.
- Partner with Security, Legal, and Privacy to translate requirements into technical policy and support audits.
- Own the IT-controlled layer for internal chatbots and agents, including gateway, identity, secrets, logging, rate limiting, and cost attribution.
- Manage inference endpoints, agent hosts, and developer AI tooling on managed devices.
- Oversee the IT-owned components of internal MCP servers, reusable agent skills, and shared agent configurations.
- Apply SRE standards to owned AI services, focusing on automation and reliability.
Requirements
- Deep expertise in two of the following three areas: production software and SRE engineering, hands-on LLM and agent work, or enterprise IT controls (identity, devices, SaaS).
- Passion for AI and staying on the bleeding edge of the field.
- Experience tuning agent behavior, running agent swarms/loops, and adapting to rapid changes in AI tools and best practices.
- Familiarity with AI platform lifecycle and governance.
- Experience designing and implementing technical policies based on acceptable-use, data-classification, and regulatory requirements.
- Experience with identity and access management, including SSO and SCIM provisioning.
- Experience building and operating allowlists for connectors and MCPs.
- Understanding of infrastructure management for AI services, including inference endpoints and agent hosts.
- Familiarity with SRE principles and applying them to AI services.