Support Engineer, AI Infrastructure & Tooling

$169k - $245k • Remote • San Francisco, CA • New York, NY • United States

Posted 1mo ago

Job Location

San Francisco, CA • New York, NY • United States

Tech Stack

Remote Work Policy

Fully remote

Categories

AI Agent Engineer

About the job

Figma is seeking a Support Engineer for its AI Infrastructure & Tooling team. This role will be the technical execution layer, bringing together support tools, customer context, internal systems, and AI workflows. You will design, build, and operationalize integrations across various systems to automate workflows, connect systems, and streamline support operations. The goal is to enhance the customer and Specialist experience by applying AI to improve support workflows, quality, and efficiency, ensuring the right context is available for issue resolution.

Responsibilities

  • Build and operationalize AI-powered workflows to improve Product Support experiences.
  • Design and maintain integrations across systems like Decagon, Zendesk, Figma admin tooling, and internal data sources.
  • Integrate relevant customer, account, product, billing, file, or admin metadata into support conversations.
  • Utilize LLMs and AI patterns for classification, summarization, routing, recommendations, context enrichment, and workflow automation.
  • Partner with cross-functional teams to align on requirements, implementation, governance, and rollout.
  • Build quality checks, monitoring, fallback paths, and operational guardrails for AI-powered workflows.
  • Define success metrics, track adoption and impact, and iterate based on outcomes and efficiency.

Requirements

  • 3+ years of experience shipping integrations, automations, or internal tools across customer-facing operational systems.
  • Strong proficiency in modern back-end technologies and languages (e.g., Ruby, Python, Go, C++, PostgreSQL).
  • Hands-on experience building APIs, implementing webhooks, orchestrating data flows, and integrating systems.
  • Hands-on experience with LLM-powered workflows, AI automations, or AI-enabled customer/support experiences.
  • Ability to translate ambiguous support problems into practical, adopted, and measurable technical solutions.
  • Proven track record of designing AI workflows with clear guardrails, fallback paths, and responsible deployment practices.

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