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PointFive is seeking a candidate to build and run an AI-powered support function that triages, diagnoses, and resolves tickets, with the AI handling first-pass interactions. You’ll measure success, escalate hard cases, and own the end-to-end learning loop in a startup environment.
Ideal candidates ship LLM agents, can wire APIs and webhooks, and write clearly for both customers and engineers. Cloud billing knowledge is a plus as the platform focuses on cost-aware AI tooling.
This role asks someone to build and run a support function as an AI system, not a ticket queue. A strong candidate has shipped LLM agents or AI tools that real users relied on, can wire up and debug APIs and webhooks, and has built evals to check agent quality before and after launch. Clear writing for both customers and engineers matters, along with the self direction to own a whole function in a startup.
The work is largely about making AI do the first pass of support: triaging, diagnosing and resolving tickets, then measuring how well that goes. What stays human is judgment on hard escalations, deciding what success looks like, and turning messy cases into fixes and documentation. The role sits where AI takes over routine support and people handle the edges and the learning loop.
Someone here would gain hands on practice building agentic support on real enterprise data, including evals, measurement and escalation design. Since the company works on cloud, data and AI token spend, exposure to billing and cost data would deepen that experience. Building this from scratch offers a rare chance to shape how AI support is done end to end.
This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.
An AI platform that finds and automatically fixes wasted cloud, data and AI agent spend before it shows up on the bill.