The engineer behind customer support. We run a self-hosted helpdesk with an AI agent on top of it, and you own that stack: the automations that take repetitive work off the team, the integrations that put order and device data in the ticket, the pipelines and dashboards that show where volume comes from. A growing share of the work is enterprise. We sell Pocket into companies now, and B2B support runs on different rails - named accounts, SLAs, admin tooling, security reviews - and most of that layer doesn't exist yet. This is a hands-on role. You sit with the support team every day and you ship your own code.
What you'll own
Our self-hosted helpdesk: uptime, upgrades, configuration, and the patches we contribute back upstream
Automations and integrations that remove manual steps - routing, macros, ticket enrichment from our order, fulfillment, and device systems
The AI support agent and the knowledgebase behind it: retrieval quality, evals, and pushing resolution rate up
The support data layer: pipelines, models, and dashboards covering volume, contact drivers, deflection, CSAT, and team performance
Analysis that turns ticket data into decisions - what's breaking, what it costs, what product needs to hear
Enterprise support infrastructure: named-account routing, SLA tracking, admin and fleet-level views, and the workflows behind security reviews and compliance requests
Account-level reporting for enterprise customers - deployment health, fleet status, usage - built once and used by support, sales, and the customer
Internal tooling for the CS team. If something is missing, you build it
What we're looking for
You've owned a service in production end to end
Strong with TypeScript and SQL, and comfortable running and debugging a self-hosted app
SQL well past the basics, and enough Python to do the analysis yourself
You've built dashboards people use
Hands-on with LLM tooling - prompts, retrieval, evals. You can tell why an AI agent gave a bad answer and fix it
You've built for business customers and you know what changes at that tier: admin roles, audit trails, SLAs, single sign-on, data handling that survives a security review
You work directly with non-technical people and turn vague operational problems into systems
Bias to ownership. You find the manual step and delete it
Bonus points for:
Time spent in or next to a support or ops team
Enterprise support tooling: SLA engines, account hierarchies, SSO, SOC 2 or HIPAA workflows
Shopify, helpdesk, or CRM API work
Consumer hardware sold into companies
What we offer
Work directly with us and learn fast
Direct impact on how the company operates day to day