AI Engineer, Internal Tools

The shape of it

In the posting’s own words

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.

What it asks for · 5

• 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

Also a plus

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

What the job covers

• 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

Tools and skills named

Words the posting leans on

• systems11×
• experience9×
• build8×
• enterprise7×
• business6×
• design6×
• production6×
• workflow6×
• agents5×
• applications5×
• engineering5×
• internal5×
• patterns5×
• platform5×
• solutions5×
• applied4×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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