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Support AI Engineer
Full-time
About the Role
Figma is evolving the Product Support experience, powered by AI, automation, and integrated systems. As a Support AI Engineer on the AI Infrastructure & Tooling team, you will be the technical execution layer that brings support tools, customer and account context, internal systems, and AI workflows together. You will design, build, and operationalize integrations across systems like Decagon, Zendesk, Figma admin tooling, and adjacent Product Support platforms.
This role is ideal for someone who can move from ambiguous support problems to working technical solutions: understanding the workflow, identifying the systems involved, building the integration or automation, validating the data flow, and measuring the impact.
What You'll Do
Build and operationalize AI-powered workflows that improve Product Support experiences for customers and internal support teams.
Design and maintain integrations across Decagon, Zendesk, Figma admin tooling, internal data sources, and adjacent platforms.
Bring relevant customer, account, product, billing, file, or admin metadata into support conversations for chatbots and Specialists.
Use LLMs and AI patterns for classification, summarization, routing, recommendations, context enrichment, and workflow automation.
Partner with Engineering, Analytics, Security, Programs, Support, and vendor teams on requirements, implementation, and rollout.
Build quality checks, monitoring, fallback paths, and operational guardrails so AI-powered workflows can be trusted in production.
Define success metrics for each workflow, track adoption and impact, and iterate based on outcomes.
We'd Love to Hear From You If You Have
3+ years shipping integrations, automations, or internal tools across customer-facing operational systems.
Strong proficiency in modern back-end technologies (e.g., Ruby, Python, Go, C++, PostgreSQL), with hands-on experience building APIs, webhooks, and data flows.
Hands-on experience with LLM-powered workflows, AI automations, or AI-enabled customer/support experiences.
Strong product and stakeholder instincts to translate ambiguous support problems into measurable technical solutions.
A proven track record of designing AI workflows with clear guardrails, fallback paths, and responsible deployment practices.
Added Pluses
Experience with support platforms like Zendesk, Decagon, Sprinklr, Gainsight, Maestro QA, Assembled, or Salesforce.
Familiarity with agent-assist tooling, AI support chatbots, copilot tooling, RAG, or AI observability.
Background in Support Engineering, Internal Tools Engineering, Solutions Engineering, or CX Systems.
Familiarity with support metrics such as containment, deflection, CSAT, and first contact resolution.
