AI Engineer, Internal Tools

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, part of FTS (our Business Technology org), helps turn that energy into meaningful impact by making it easier for every Figmate, from Sales and Support to Finance, People, and Legal, to safely adopt AI and use it to improve how they work. 

We’re a small, high-leverage team organized around three pillars: Platform & Tooling, Infrastructure & Hosting, and Applied AI Builds, and this role is a key member of the Applied AI Builds pillar.

As an AI Engineer, Internal Tools, you’ll work directly with teams across Figma to identify high-value AI opportunities and take them to production, moving from understanding a business workflow, to rapidly prototyping an approach, to evaluating it and integrating it with the systems and data needed to make it useful in the real world. 

This isn’t a role focused only on building AI demos: you’ll own solutions through production, help determine where AI adds value and where traditional rules-based software is the right choice, and shape how agents can safely take actions across enterprise systems. As common patterns emerge, you’ll partner with our Platform & Tooling and Infrastructure teams to build reusable capabilities that make future AI builds faster and safer.

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:

• Partner directly with teams across GTM, Finance, People, Legal, Support, and other business functions to understand workflows and identify high-value opportunities for AI

• Design, build, and productionize AI agents, assistants, and workflow automations that solve real business problems using LLMs, tool calling, RAG, structured outputs, agent frameworks, MCP, APIs, and enterprise data

• Integrate AI applications with enterprise systems and data sources across GTM, Finance, People, Support, and internal APIs

• Build evaluations and feedback loops to measure accuracy, reliability, and business impact before and after AI solutions reach production

• Design deterministic guardrails, human-in-the-loop controls, and approval patterns for workflows where AI systems take business-critical actions

• Build production-ready systems with strong observability, failure handling, security, authentication, authorization, and auditability

• Identify reusable patterns across individual AI projects and build them out as shared components and capabilities in partnership with our Internal AI platform teams

• Help define how Figma approaches Applied AI engineering and scales AI adoption across the company

We’d love to hear from you if you have:

• 5+ years of software engineering experience building production applications, integrations, backend systems, or AI-powered products

• Hands-on experience building applications with LLMs, agents, retrieval-augmented generation, function calling, schema-constrained outputs, or evaluation frameworks

• Experience taking an AI application or workflow beyond a prototype and operating it in a production environment

• Strong API, integration, and system design fundamentals, with experience connecting applications across multiple systems and data sources and strong engineering judgment about when to apply AI and when a rules-based approach is the right choice, and experience designing reliable production systems with appropriate observability, failure handling, authentication, authorization, and security controls

• Experience working directly with non-engineering stakeholders to understand ambiguous business problems and translate them into technical solutions and ability to move quickly from discovery to prototype while understanding what is required to safely and reliably productionize a solution

While it’s not required, it’s an added plus