AI Engineer, Internal Tools
$153k - $296k • Remote • San Francisco, CA • New York, NY • United States
Posted 7h ago
Job Location
San Francisco, CA • New York, NY • United States
Tech Stack
Remote Work Policy
Fully remote
Categories
AI Engineer
About the job
Figma is seeking an AI Engineer for its Internal AI team, which focuses on making AI adoption easier and more impactful for all Figmates across various departments like Sales, Support, Finance, People, and Legal. This role is a key part of the Applied AI Builds pillar, responsible for identifying high-value AI opportunities, prototyping solutions, and taking them to production. You will work directly with teams to understand business workflows, build AI agents and automations, integrate them with enterprise systems, and ensure their safe and reliable operation. This position involves owning solutions through production, determining the appropriate use of AI versus traditional software, and shaping how agents can safely interact with enterprise systems. You will also collaborate with platform teams to build reusable AI capabilities and help define Figma's approach to Applied AI engineering.
Responsibilities
- Partner with cross-functional teams to understand workflows and identify AI opportunities.
- Design, build, and productionize AI agents, assistants, and workflow automations using LLMs, RAG, tool calling, and other AI techniques.
- Integrate AI applications with enterprise systems and data sources.
- Develop evaluations and feedback loops to measure the accuracy, reliability, and business impact of AI solutions.
- Design guardrails, human-in-the-loop controls, and approval patterns for AI systems performing critical actions.
- Build production-ready systems with robust observability, failure handling, security, and auditability.
- Identify and build reusable AI patterns as shared components in partnership with platform teams.
- Contribute to defining Figma's Applied AI engineering strategy and scaling AI adoption.
Requirements
- 5+ years of software engineering experience building production applications, integrations, backend systems, or AI products.
- Hands-on experience building applications with LLMs, agents, RAG, function calling, or evaluation frameworks.
- Experience taking an AI application or workflow from prototype to production.
- Strong API, integration, and system design fundamentals.
- Experience connecting applications across multiple systems and data sources.
- Strong engineering judgment regarding the application of AI versus rules-based approaches.
- Experience designing reliable production systems with appropriate observability, failure handling, authentication, authorization, and security controls.
- Ability to work with non-engineering stakeholders to understand business problems and translate them into technical solutions.
- Ability to move quickly from discovery to prototype while understanding productionization requirements.