Senior Full-Stack Engineer (React + Node.js)

What You Will Build

• Usage & analytics dashboard — real-time and historical consumption analytics for Location Services (mapping, geocoding, routing, traffic), filterable by service, app, and region
• Geography analytics — location-aware visualization of where geocodes and analyses actually happen, rendered on Maps with heatmaps/clusters and time-scrubbing
• Cost & billing module — usage forecasting, spend attribution by service/region/app, commercial model comparison (transaction / user / asset)
• Data Explorer — filterable export of aggregated usage data (daily level) for external analysis in Tableau or similar tools
• AI Services Analyst — natural language queries against live usage data (MVP: textual answers; roadmap: custom reports, automated agents)
• REST API layer (Node.js) consuming BAM (Billing, Accounting & Metrics) system APIs built on top of aggregated Splunk data

What project we have for you

Our client is building the Analytics Portal — a SaaS platform that gives external organizations consuming Location Services APIs self-service access to consumption intelligence. HLS Analyst is the second app within this portal, designed for enterprise customers who need more than basic usage monitoring — they need actionable analytics to optimize spend, govern consumption, and drive growth.

Intellias is the delivery partner. You will work closely with the Client’s Product Owner, Technical Lead, and Engineering Manager.

What you will do

• Implement and maintain React frontend components — map-based UI, dashboards, data visualizations
• Build Node.js backend services — API layer, integration with data APIs and ArcGIS Enterprise
• Collaborate with Principal Backend Engineer on architecture decisions and data contracts
• Participate in requirements clarification with BA/AI PM — translate specs into technical solutions
• Contribute to code reviews and maintain code quality standards
• Work with DevOps on AWS deployment pipelines and environment configuration
• Raise technical risks and blockers early — lean team, no room for silent blockers

What you need for this

Mandatory Requirements

• Overall JavaScript experience 7+ years
• proficiency in React/NodeJS
• AWS — hands-on experience (EC2/ECS, S3, Lambda or similar services)
• TypeScript — confident daily usage
• SQL — independent query writing for data verification and debugging
• Experience consuming third-party geospatial or data APIs
• Hands-on experience with AI coding agents — Cursor, Claude Code, GitHub Copilot, Codex, or similar; actively used in daily development, not just tried once
• Hands-on experience with at least one LLM provider API (OpenAI, Anthropic, or similar) — direct work with endpoints, parameters, and structured outputs, not only via high-level wrappers
• Experience building chat or AI-assisted UI — streaming responses (SSE or WebSocket), message history management, loading and error states specific to LLM latency
• English — B2+, able to participate in client calls and async written communication

Nice to Have

• Geospatial data processing — working with large spatial datasets, coordinate systems, tiling, or spatial aggregation (e.g. H3, S2, quadkeys)
• Map rendering experience — HERE Maps SDK, Mapbox GL JS, deck.gl, Leaflet, or any WebGL-based mapping library; understanding of rendering performance trade-offs
• Experience with ArcGIS REST APIs or similar GIS platforms
• RAG pipeline integration from the frontend — connecting to vector search APIs, passing context chunks, displaying sources
• MCP (Model Context Protocol) — familiarity with client/server concepts; experience with MCP-compatible tooling
• Agentic UI patterns — multi-step flows, tool call visualization, human-in-the-loop confirmation screens
• Spec-driven development — working from detailed API contracts or functional specs; writing or consuming OpenAPI/Swagger definitions
• Public sector or traffic/mobility domain background
• Experience working from UI prototypes (Lovable, Figma) to production code

AI-Driven Development — How We Work

This team operates as an AI pod — AI tooling is part of the daily engineering workflow, not an optional extra. We expect engineers to actively use AI assistants for coding, debugging, code review, and documentation, and to continuously experiment with new tools as they emerge.

We are looking for people who are genuinely curious about AI-assisted development and want to push the boundaries of what a lean team can deliver.

• Daily use of AI coding assistants — Cursor, GitHub Copilot, or equivalent; you should already have a preferred setup
• Experience using LLMs for code generation, refactoring, and test writing — not just autocomplete
• Comfortable working with AI-generated code — able to review, validate, and own it
• Experience or strong interest in agentic development workflows — Claude Code, Devin, or similar
• Proactive about learning new AI tooling — this space moves fast and we move with it

What it’s like to work at Intellias

At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth.

We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law.

We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success.