Support Engineer, AI Infrastructure

The shape of it

In the posting’s own words

You'll design, build, and operationalize integrations across systems like Decagon, Zendesk, Figma admin tooling, and adjacent Product Support platforms. Your work will help us bring the right context into customer conversations, automate complex workflows, and optimize both the customer and Specialist experience by applying AI where it can meaningfully improve support workflows, quality, and efficiency.

What it asks for · 5

• 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

Also a plus

• 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

What the job covers

• 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

Tools and skills named

Words the posting leans on

• support19×
• workflows16×
• experience11×
• systems10×
• customer8×
• product7×
• automation6×
• internal6×
• tooling6×
• design5×
• bring4×
• building4×
• context4×
• data4×
• engineering4×
• integrations4×

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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