Lead Frontend Engineer
Core
Own frontend architecture and build production conversational UIs, developer portals, and self-service platform experiences for AI applications.
Role type
Lead Frontend Engineer (AI Platform)
Builds
Production conversational UIs, AI component libraries, developer portals, and self-service platform experiences.
Domain
Artificial Intelligence / Cloud Infrastructure
Deliverable
production ML models
Required skills
React, Next.js, TypeScript, Node.js, Vertex AI, Gemini, Google ADK, LangChain.js, RAG systems, SSE, WebSockets, OAuth2, API gateways, Kubernetes, GKE, Jest, React Testing Library, Playwright, Storybook, FastAPI, BigQuery, Vertex Vector Search, GitHub Actions, Cloud Build, Cloud FinOps
Preferred skills
Self-service engineering, platform engineering, deterministic testing strategies, cloud infrastructure cost optimization
Technologies
React, Next.js, TypeScript, Node.js, Vertex AI, Gemini, Google ADK, LangChain.js, RAG, SSE, WebSockets, OAuth2, API gateways, Kubernetes, GKE, Jest, React Testing Library, Playwright, Storybook, FastAPI, BigQuery, Vertex Vector Search, GitHub Actions, Cloud Build
Responsibilities
Own frontend architecture, technology standards, component architecture, state management, rendering strategy, performance budgets, and accessibility for AI Platform UI surfaces. Build production conversational UIs with streaming responses, multi-agent trace visualization, citation and grounding displays, tool-call transparency, feedback widgets, and graceful fallback states. Develop and maintain a versioned, themeable AI component library and design system documented with Storybook for use across multiple product squads. Create golden-path frontend templates, starter kits, developer portal experiences, and service catalog entries that enable teams to self-provision AI UIs and resources. Build full-stack features across React applications, BFF services, orchestration layers, Google ADK workflows, Vertex AI Gemini, RAG systems, and vector search. Implement secure OAuth2 and API gateway integrations, including authentication, authorization, token refresh, session handling, and role-based UI rendering. Develop SSE and WebSocket streaming experiences for token-level responses, agent states, tool execution progress, and low-latency interactions. Establish component, end-to-end, deterministic-mocking, observability, telemetry, feedback, and performance practices for AI interfaces. Deploy frontend and BFF services on Kubernetes and GKE using CI/CD, progressive delivery, and environment promotion practices. Partner with platform, infrastructure, backend, product, architecture, and IT operations teams to improve developer experience, platform adoption, cost efficiency, and self-service capabilities. Own platform roadmap reviews, versioning, deprecations, adoption metrics, developer satisfaction, time-to-first-deploy metrics, and governance guardrails.
Seniority
Senior, hands-on IC
