Spatial AI Engineer

Section 1. About BigGeo

BigGeo is the Spatial Cloud.

We help companies manage and access the world’s spatial data.

Any size, any slice, any insight.

Delivered in seconds.

The Spatial Cloud is the infrastructure layer that makes spatial data accessible to any company, at any scale, delivered in seconds. We help organizations manage and access the world's location data so their teams and AI systems can make big moves with confidence.

We're building something that hasn't existed before: a new layer of the internet where the "where" and "when" behind every decision is instantly clear, programmable, and actionable. Our platform removes the complexity that has kept spatial data locked in silos for decades — and replaces it with speed, precision, and control.

We're a Calgary-based company, early and moving fast, with real customers, real infrastructure, and a clear point of view on where the world is going.

Section 2. Why BigGeo Exists and Why People Build Here

Most companies are spatially blind. They know what their data says, but not where or when things actually happen. That gap costs real money, creates real risk, and limits what AI can actually do in the physical world.

BigGeo exists to close that gap.

We’re not building another tool. We’re building the rails that connect the planet’s moving data to the systems that run the world. That’s a big problem, and it takes people who care about doing things right, not just fast.

People build here because:

• The problem is real and the category is open. We’re not competing for the middle of an existing market, we’re defining a new one. Your work shapes what the category becomes.
• Your fingerprints are on the architecture. We’re at the stage where the decisions you make today become the foundation tomorrow. What you ship matters.
• We run on clarity, not politics. We move with purpose. No bureaucratic drag, no HiPPO decisions, just a team that agrees on the mission and gets to work.
• You’ll grow fast because the problems are hard. Spatial data at scale is a genuinely difficult domain. If you want to be stretched, you’ll be stretched.

Section 3. The Role

The Spatial AI Engineer builds the applications and services that put geospatial AI to work. You will design, build, and ship full stack systems on top of The Spatial Cloud — connecting AI models and agents to the world's spatial data, and turning that combination into products that answer real questions about the physical world in seconds. This is an intermediate-to-senior position for a strong full stack developer first.

You won't be inventing new model architectures; you will be implementing geospatial AI solutions: building the interfaces, APIs, and services around AI capabilities, querying large spatial datasets, and shipping them to production.

What You Will Build and Own

As a Spatial AI Engineer, you will contribute to and own systems that include:

Your day to day:

• 80% building geospatial AI solutions. Full stack development and AI integration together: the applications, APIs, and interfaces that deliver spatial intelligence, and the LLMs, agent frameworks, and inference services wired into them.
• 10% data engineering. Preparing and moving spatial data so your solutions have what they need.
• 10% DevOps. Deploying, monitoring, and scaling what you ship.

The experience mix we are looking for:

• 60–70% full stack development. Your core strength: designing, building, and shipping production applications end to end.
• 20% AI integration. Hands-on experience wiring LLMs, agent frameworks, or inference services into real products.
• 10% data engineering. Comfortable building and maintaining data pipelines.
• 10% DevOps. Able to deploy, monitor, and operate what you build.

Required Qualifications

• 3 to 7 years of experience building and shipping production software, with strong full stack experience.
• Bachelor's degree in Computer Science, Engineering, or a related field.
• Strong programming experience in TypeScript (primary), including a modern frontend framework (React or equivalent) and Node.js backend services.
• Experience integrating AI capabilities into production applications: LLM APIs (Claude, OpenAI, or equivalent), agent frameworks, RAG, or inference services.
• Experience designing and building APIs that other developers or systems depend on. Working knowledge of SQL and hands-on experience with data pipelines.
• Comfort operating in cloud-native environments: containers, CI/CD, and at least one major cloud platform.
• Demonstrated ability to collaborate across engineering, data, and product teams and to own outcomes, not just tickets. AI-assisted coding as part of your daily workflow: you use tools like Claude Code, Cursor, ChatGPT, or Copilot to design, build, debug, and test — this is a requirement, not a bonus.

Preferred Qualifications

• Experience working with geospatial or location-based datasets in a production context.
• Familiarity with map rendering and visualization libraries (MapLibre, Mapbox GL, deck.gl, or similar).
• Familiarity with spatial indexing techniques (such as H3, S2, quadtrees, R-trees) and common geospatial data formats (GeoJSON, GeoParquet, PMTiles, FlatGeobuf, or similar).
• Experience training or fine-tuning LLMs. Experience deploying and serving LLMs in production (self-hosted inference, GPU infrastructure, or managed platforms).
• Experience with real-time systems, streaming pipelines, or event-driven architectures.
• Experience with Python, Rust, or Go for backend or performance-critical components.
• Contributions to open-source AI, geospatial, or data infrastructure projects.
• Product insight: you think beyond the ticket to the user and business problem behind it, and let that shape what you build.

Section 4. Work Environment

BigGeo is an in-office team. We build in person, think out loud, and move faster together than we ever could apart.

Section 5. Perks of Working at BigGeo

We take care of the people who build here. That means keeping things simple, human, and worth showing up for.

• Free refreshments and snacks, every day. The office is stocked, fuel yourself without thinking about it.
• Downtown Calgary location. We’re right in the heart of the city, steps from a wide range of cafes, restaurants, and eateries. Lunch options are never a problem.
• Regular off-site team activities. We get out of the office and spend time together as a team, not as a box-ticking exercise, but because we actually like the people we work with.