Responsibilities

- Build full stack features across the AI Catalog/Solution Registry web app (Next.js/React/TypeScript) and its backend services - from UI to API to data model
- Build agents, skills, and MCP servers that expose Solution Registry capabilities (register, discover, link assets, check AIRB/governance status) to agents and to the web UI alike
- Design channel-agnostic APIs so the same backend capability powers the web app, a coding-assistant integration, and a chat/search surface without a rebuild per surface
- Ship agent-facing experiences in the web app - e.g., AIRB review flows, solution detail pages, registered-asset visualizations - backed by real registry data and agent-generated recommendations
- Deliver integrations into enterprise chat/search surfaces (Teams, Slack, enterprise search) using their bot frameworks/connectors, reusing the same backend capabilities built for the web app
- Design MCP tools with proper auth, scoping, and audit, and build the front-end/back-end plumbing to surface that governance state to users (e.g., what an agent did, on whose behalf)
- Build evaluation/observability tooling - both the backend harness that scores agent behavior and the UI/dashboard a reviewer uses to see results and approve autonomy upgrades
- Work day to day inside AI coding assistants (Claude Code, Codex, Copilot) and contribute to the tooling that lets other engineers do the same
- Partner with platform, security, and governance teams so data model, API,



and UI choices are compliant by default
- Comply with all applicable Company policies, procedures, and business directives, changes including those relating to work location, team assignments, work schedules, and flexible work arrangements

Required Qualifications

- Undergraduate degree or equivalent experience
- 4+ years of full stack production engineering: strong in both a up-to-date frontend framework (React/Next.js, TypeScript) and backend services (Python or Node/TypeScript)
- Experience designing and consuming REST/GraphQL APIs, including schema/versioning discipline
- Hands-on experience building with or on top of LLMs - agents, RAG, prompt-based features, or tool-calling - in a shipped product
- Experience with cloud deployment (AWS, Azure, or GCP) and standard web app infra (containers, CI/CD)
- Experience building MCP servers or similar tool/plugin integrations for LLM agents
- Experience integrating with enterprise chat/search bot frameworks (Teams, Slack, enterprise search connectors)
- Experience building internal admin/review tooling for governance or compliance workflows (approval flows, audit views)
- Familiarity with SQL/relational data modeling for registry-style entities (solutions, assets, governance metadata)
- Familiarity with evaluation frameworks for non-deterministic (agent) systems
- Comfort owning a feature end-to-end: data model - API - UI, without needing a dedicated backend or frontend counterpart for every task

📌 Lead Full Stack Engineer (Bengaluru)
🏢 Optum
📍 Bengaluru