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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Support Engineer, AI Infrastructure - **Company:** Figma, Inc. - **Location:** New York, United States - **Experience:** Experienced - **Salary:** $169,000.0 - $245,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Business Systems, C++ (Programming Language), Software Debugging, Python (Programming Language), PostgreSQL, Operational Data Store, Ruby, Salesforce.Com, Screen Reader, Data Streaming, Systems Integration, Chatbots, Large Language Models, Figma, Operational Systems, Api Design, Zendesk, Webhooks, Automation Anywhere, Golang - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/support-engineer-ai-infrastructure-figmadesign-9020812 ## About the Role * 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), with hands-on experience building APIs, implementing webhooks, orchestrating data flows, and integrating systems across complex workflows. * Hands-on experience with LLM-powered workflows, AI automations, or AI-enabled customer/support experiences, including working with operational data to debug issues, improve workflows, and measure impact * Strong product and stakeholder instincts: you can 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, * Experience with support platforms like Zendesk, Decagon, Sprinklr, Gainsight, Maestro QA/Rippit, Assembled, Salesforce, or similar systems * Familiarity with agent assist tooling, AI support chatbots, copilot tooling, RAG, AI observability, or monitoring AI workflows in production * Experience building internal Slack tooling, workflow automations, or embedded support experiences * Background in Support Engineering, Internal Tools Engineering, Solutions Engineering, Support Operations, CX Systems, or Business Systems * Familiarity with customer support metrics such as containment, deflection, CSAT, first contact resolution, routing accuracy, Job level and actual compensation will be decided based on factors including, but not limited to, individual qualifications objectively assessed during the interview process (including skills and prior relevant experience, potential impact, and scope of role), market demands, and specific work location. ## Description * 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 Product Support platforms * Bring relevant customer, account, product, billing, file, or admin metadata into support conversations so chatbots and Specialists have the context they need to resolve issues more effectively * 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 to align on requirements, implementation, governance, 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 customer outcomes, Specialist efficiency, and adoption, * Holding interviews in an accessible location * Enabling closed captioning on video conferencing * Ensuring all written communication be compatible with screen readers * Changing the mode or format of interviews To ensure the integrity of our hiring process and facilitate a more personal connection, we require all candidates keep their cameras on during video interviews. 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