Overview

Build the CI&D quality gates for backend and AI workflows so engineers get faster, more trustworthy signals before changes reach production.

Create reusable validation infrastructure for AI-powered backend features, including scenario-based evals, staging validation flows, generated test profiles, and higher-signal end-to-end checks.

Improve the feedback loop between development and production by connecting eval results, CI outcomes, runtime telemetry, and member-facing signals into one operational picture.

Help standardize the shared LLM delivery surface in practice: unified client patterns, trace capture, environment setup, and operational guardrails that feature squads can adopt without bespoke platform work.

Partner closely with backend engineers, AI engineers, PMs, and adjacent platform teams to turn release-confidence needs into reusable workflows that scale across the platform rather than one-off fixes for a single squad.