IT Engineer, Internal AI Infrastructure

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About the role

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! Figma employees are among the most AI-active in the industry, and our Internal AI team exists to make that energy compound rather than fragment. Sitting within FTS (our Business Technology org), the team owns the shared rails for employee-facing AI: the platforms that lets every Figmate, from sales to recruiting to finance, build and use AI tools that are governed, reliable, and reusable. We're a small, high-leverage team organized around three pillars: Platform & Tooling, Infrastructure & Hosting, and Applied AI Builds. This role anchors the Infrastructure & Hosting pillar. This is the runtime layer everything else depends on. You'll design and build the paved path that takes an internal AI app, bot, or agent from prototype to production: shared hosting and execution infrastructure, model routing that directs each task to the right model based on cost and capability, and the telemetry, audit, and cost-attribution layer that gives our security and finance partners visibility no one at Figma has today. You'll work closely with our IT Engineering team on identity and access patterns, with Security on guardrails for sensitive-data workflows, and with the AI infrastructure teams building Figma's product to share gateways and avoid duplicate layers. This is a full time role that can be held from one of our US hubs or remotely in the United States. What you'll do at Figma: • Design and build the hosting golden path for internal AI applications, bots, and agents, including runtime patterns for long-running workflows, scheduled jobs, and agent execution • Build the model routing layer that directs tasks across frontier and lower-cost models based on cost, capability, and policy with a full audit trail • Stand up observability, usage analytics, audit logging, and per-team cost attribution for AI workloads across the company • Integrate identity, access, and security patterns (Okta-connected by default) so every internal AI app is safe on day one, including the sanctioned path for workflows touching customer, financial, or people data • Partner with engineers on our product AI infrastructure teams to share gateways and telemetry rather than building parallel systems • Help shape the team's platform strategy, roadmap, and engineering best practices as a founding member of the infrastructure pillar We'd love to hear from you if you have: • 5+ years of software engineering experience, with significant time in infrastructure, platform, or backend engineering • A track record of building internal platforms or paved paths that other engineers and teams adopted, not just maintained, with excellent communication skills collaborating across security, IT, and business teams • Strong system design skills and experience architecting resilient, observable production systems • Hands-on experience with LLM operations: model gateways or routing, agent runtimes, evals, or cost/usage instrumentation • Experience with identity and access management in an enterprise environment (e.g., Okta, SSO, secure service-to-service auth) While it's not required, it's an added plus if you also have: • Experience building internal AI platforms or workspaces (the Ramp Glass / JPMorgan LLM Suite category) or developer platforms at a comparable scale • Familiarity with MCP, agent orch

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