Figma
Software Engineer - AI Platforms
About this role
Figma is seeking experienced Software Engineers to build foundational AI platforms and infrastructure that power design and collaboration features across the company. You'll work on specialized teams—Modeling Platform, Agent Platform, Search & Recommendations, Make Platform, or Extensibility—designing scalable systems for AI model development, agentic workflows, and developer integrations.
What you'll do
- Design and build scalable, reliable AI infrastructure and platforms supporting end-to-end feature development
- Collaborate with product, research, and infrastructure teams to develop cutting-edge AI capabilities
- Debug and resolve complex production issues spanning multiple services and system layers
- Shape platform strategy, roadmaps, and engineering best practices across the organization
- Mentor engineers and foster technical excellence and collaboration
- Partner with teams to improve performance, reliability, and quality of AI systems
What they're looking for
- Backend or infrastructure engineering
- TypeScript, Python, or Ruby
- System design and architecture
- AI/ML systems or search infrastructure experience
- Distributed systems
- Production systems reliability
- Developer platform experience
- Problem-solving across multiple system layers
Benefits
- Full-time role based in San Francisco or New York, or remote within the US
- Work on cutting-edge AI and design collaboration technology
- Mentor and collaborate with world-class engineering teams
- Shape the future of design accessibility and product development
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Figma
Figma is a design platform that leverages AI and machine learning to power intelligent features like search, ranking, and generative capabilities. The company is hiring software engineers, ML engineers, and support specialists to build scalable infrastructure, AI-powered automations, and support systems that serve millions of users.
- Website
- figma.com
Likely interview questions
- Tell us about a time you designed and built a scalable backend system or platform that needed to support multiple teams. What were the key architectural decisions you made?
- Describe your experience with AI infrastructure or developer platforms. How did you approach building abstractions that other engineers could build on top of?