Full-Stack Developer

Help build the tools that businesses use to decide where to grow.

At PiinPoint, a Y Combinator-backed company, we help retailers, restaurant brands, and commercial real estate teams evaluate locations and plan their networks. Our products bring together demographics, mobility data, predictive models, and interactive maps to help customers make decisions with real consequences for their businesses.

We’re looking for a full stack developer who enjoys making complex data useful. You’ll build across our Python and React stack, solve geospatial performance challenges, and help develop AI-powered tools that make location analysis more accessible.

The team and opportunity

We’re a small, experienced, remote team where developers work directly with product, design, data science, and company leadership. You’ll contribute to technical decisions, understand the customer problems behind your work, and see features through from early ideas to production.

PiinPoint has grown from its Y Combinator beginnings into an established platform that customers rely on. Our next chapter combines improving that foundation with building new ways to explore data and complete analysis using AI. The engineering challenge spans both: making existing workflows faster and more intuitive, and figuring out what new capabilities should look like.

What you’ll be working on

• Make complex analysis intuitive. Build interactive maps, visualizations, and workflows that help customers evaluate potential locations and understand their markets.
• Build across the full stack. Develop React interfaces, Python APIs, application logic, and database queries, taking responsibility for how they work together.
• Bring AI into useful customer workflows. Help users explore datasets, interpret results, and complete multi-step analysis, with attention to permissions, validation, and reliability.
• Solve spatial and data performance problems. Improve how we query, process, and display large geospatial datasets, from demographic polygons to business locations and mobility data.
• Improve an established product. Modernize components, upgrade dependencies, and strengthen architecture while continuing to deliver customer-facing improvements.
• Own quality through delivery. Prototype ideas, review code, write meaningful tests, deploy changes, and troubleshoot production issues.

Your first 90 days

We’ll shape your initial projects around your experience and the team’s priorities. Here’s what a successful start could look like:

• First 30 days: Learn our product and development workflow, trace a location analysis from the interface through the API and database, and ship a scoped improvement with support from the team.
• By day 60: Own a feature or performance improvement across the stack, working with product and design to define the approach, implement it, and release it.
• By day 90: Take a larger piece of work from problem definition through delivery, evaluate the results, and contribute recommendations for the next iteration.

Technologies we use

• Back end: Python and Python web frameworks
• Front end: JavaScript, React, Redux, MapLibre, HTML, and CSS
• Databases: PostgreSQL and MongoDB
• Spatial technologies: PostGIS, GeoPandas, Shapely, and GDAL
• Infrastructure: AWS, Docker, Kubernetes, and Convox

What we’re looking for

• Experience shipping and maintaining web applications with Python and React.
• Strong JavaScript, HTML, and CSS fundamentals, with care for usable, responsive interfaces.
• Experience designing and integrating APIs, including validation, authentication, and error handling.
• Practical database experience, including data modelling and query optimization.
• Experience with interactive mapping or geospatial applications, and familiarity with concepts such as spatial queries, indexing, and coordinate systems.
• Ability to take a feature from an initial problem through implementation, testing, deployment, and iteration.
• Good judgment about technical trade-offs, including when to prototype and when to invest in a more durable solution.
• Comfort using AI development tools while taking responsibility for understanding, reviewing, and testing the resulting code.
• Clear communication and the ability to work independently within shared priorities, collaborate on difficult problems, and raise blockers early.

Nice to have

• Experience with MapLibre, Mapbox GL JS, Leaflet, or similar mapping libraries.
• Deeper experience with PostGIS, GeoPandas, Shapely, or GDAL.
• Experience integrating LLMs, AI agents, or other AI-powered capabilities into production applications.
• Experience with large datasets, background jobs, or data processing pipelines.
• Familiarity with AWS, containers, CI/CD, and application monitoring.
• Experience improving an established SaaS application while continuing to deliver new features.

You don’t need experience with every tool in our stack. We value strong fundamentals, thoughtful problem-solving, and the ability to learn.