AI Engineer, Internal Tools

Location: San Francisco, CA; New York, NY; United States, or remote in the United States. Canada is also listed as an available location. In-person onboarding is required.

Annual base salary: $153,000–$296,000 USD.

Company

Figma develops a collaborative design platform that helps teams create prototypes, translate designs into code, and use AI in real-time workflows.

What you will do

• Partner with GTM, Finance, People, Legal, Support, and other functions to identify high-value AI opportunities and understand business workflows.
• Design, build, and productionize AI agents, assistants, and workflow automations using LLMs, tool calling, RAG, structured outputs, agent frameworks, MCP, APIs, and enterprise data.
• Integrate AI applications with enterprise systems, data sources, and internal APIs.
• Build evaluations and feedback loops to measure accuracy, reliability, and business impact before and after production deployment.
• Design deterministic guardrails, human-in-the-loop controls, approval patterns, observability, failure handling, security, authentication, authorization, and auditability for business-critical workflows.
• Identify reusable patterns, build shared capabilities with Internal AI platform teams, and help define how Applied AI engineering scales across Figma.

Requirements

• 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 production.
• Strong API, integration, and system design fundamentals, including connecting applications across multiple systems and data sources.
• Engineering judgment about when to apply AI and when a rules-based approach is appropriate.
• Experience designing reliable production systems with 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.
• Ability to move from discovery to prototype while understanding how to safely and reliably productionize a solution.

Nice to have

• Background building internal AI applications or working in Applied AI, Forward Deployed Engineering, or AI Solutions Engineering.
• Experience with MCP, agent orchestration frameworks, and enterprise tool-calling patterns.
• Knowledge of AWS Bedrock, AgentCore, OpenAI, Anthropic, or similar AI platforms.
• Experience integrating Salesforce, Zendesk, Workday, NetSuite, Greenhouse, Slack, or similar enterprise systems.
• Knowledge of AI evaluations, observability, prompt and version management, and human-in-the-loop systems.
• Experience implementing Okta, SSO, OAuth, and secure service-to-service authentication within Security, Privacy, SOX/ITGC, or other enterprise governance requirements.

Culture & Benefits

• Remote work is available in the United States, with options to work from US hubs.
• Health, dental, and vision coverage, retirement benefits with company contributions, paid parental leave, and reproductive or family planning support.
• Mental health and wellness benefits, paid time off, paid sick leave, holidays, and flexible PTO for eligible exempt employees.
• Equity, annual bonus eligibility for non-sales roles, and possible recharge days, cell phone and home internet reimbursements, and lifestyle spending accounts.
• Commitment to equal employment opportunities, reasonable accommodations, and continuous learning through the “Grow as you go” value.

Hiring process

• Interview evaluation considers qualifications, skills, relevant experience, potential impact, role scope, and work location.
• Video interviews require candidates to keep their cameras on.
• In-person onboarding is required if hired.