Principal Engineer — AI (contract)
Principal-level contract engineering, most recently owning the AI capability of an HR-tech SaaS end to end: the agentic layer of the product — an in-app copilot with tool-calling over live customer data, autonomous document-generation pipelines, and the server-side compute services underneath — while shipping across the full stack (PHP/GraphQL, React, Go gateway, edge services).
- Built an in-app AI copilot: multi-provider tool-calling agent (Anthropic + OpenAI via Vercel AI SDK) with data-query and mutation tools, an LLM-as-judge quality gate scoring every response on 8 dimensions, and SSE keep-alive for long agent streams
- Designed an autonomous report pipeline — one model plans the document, Claude Agent SDK runs write it against live data, a second agent pass compiles branded slide decks via a 90+ layout PPTX compiler with chart rasterization and LaTeX PDF output, agents running in a parallel containerized fleet
- Moved heavy analytics server-side (Bun + Hono behind a Go gateway): pure-function ports oracle-verified for numeric parity with the client engine, event-keyed Redis caching, validated at 20k+ entity scale
- AI data enrichment: ingested a ~32-table public occupational dataset, LLM-classified it into customer data structures, and built persona-driven simulation commands generating realistic test data at scale
- Shipped a standalone real-time collaborative app on Cloudflare Workers + Durable Objects — WebSocket presence, optimistic updates with server reconciliation, embedded AI assistant with client-side tool execution
- Hunted down multi-user concurrent-edit data loss with a purpose-built integrity harness: truly-parallel mutation racing, event-chain fork detection, contract tests driving real client reducers against the live API