Senior Frontend Developer- AI Native Data

What you'll do

• Build React and TypeScript features across data explorers, topic pages and natural-language search.
• Create interactive D3.js/SVG visualizations (choropleth maps, timelines, scatter plots, ranking tables) with zoom, brushing, tooltips and linked charts.
• Design AI-native interfaces: conversational query UIs, streaming LLM answers, and agent workflows that show plan steps, tool calls, progress and cited sources.
• Build generative UI, where model output selects and fills real chart and table components, with fallbacks, error states and user controls.
• Integrate with Flask and Mixer APIs, and keep chart and query state in the URL for shareable links.
• Ship responsive, accessible (WCAG) and fast UI, with tests, through GitHub pull requests.

Must-have skills

• 8–12 years of professional frontend development.
• Strong TypeScript and JavaScript (ES6+, async/await).
• Production React: hooks, state, component architecture.
• CSS/SCSS, Flexbox/Grid, responsive layouts, accessibility.
• Data visualization with D3.js and SVG.
• REST/JSON APIs and client state, including URL serialization.
• Built at least one LLM-powered UI (chat, AI search, copilot or agent) [must-have or nice-to-have: TBD].
• Jest, React Testing Library, Git/GitHub PRs; professional English [level: TBD].

Nice to have

• Agentic UX: human-in-the-loop approvals, multi-step progress, cited answers, handling model uncertainty.
• Gemini API, Google ADK, Model Context Protocol (MCP).
• Prompt design and evaluating AI features (quality, latency, feedback).
• Python/Flask, gRPC/Protobuf.
• Knowledge graphs: StatVars, DCIDs, provenance; Schema.org, MCF, JSON-LD, RDF.
• Webpack, npm/yarn, Bazel; Percy and hermetic E2E tests.
• Docker, GCP (GKE); open-source contributions.