Senior / Staff Backend Engineer, Maps

About Radar

Radar is the global leader in geolocation, with geofencing SDKs, maps APIs, and AI-enabled solutions for marketing, fraud, and operations teams. We're trusted by some of the world's best companies, from high-growth startups to the Fortune 500. We process over 1 billion API calls per day from hundreds of millions of devices. We've raised $85.5M from world-class investors, including Accel and Insight Partners. We have a high-performance culture with ambitious and entrepreneurial teammates in every role. We recently moved into an amazing new office in Flatiron, Manhattan, NYC, and were named a top 10 best place to work in NYC by Crain's.

About The Role

We're looking for a Maps Product Engineer to strengthen the data foundation behind Radar's geocoding platform. You'll own the systems that bring many sources of location data together into something reliable, accurate, and fresh, with the opportunity to bring AI into how we enrich and scale it. This role will be in our NYC HQ.

How We Work

Most of our engineering team are former technical co-founders or former Radar interns from schools like Waterloo and CMU. Most engineers fit one of two molds: Staff level expertise in one stack, or "Multi-Stack" at any level. A desire to learn, jump around to different stacks, and get things done is important. We care about shipping fast and talking to customers. Working together in-person in our NYC HQ is the fastest way for us to get things done. We meet on Mondays to plan work in small groups and use Linear for planning. We expect to ship big things every week.

The Stack

• Core backend service: HorizonDB, a geospatial database written in Rust that powers geocoding
• Indexing: Tantivy, RocksDB, and FSTs, with ML models for query understanding and ranking
• Geospatial data pipelines: Scala and Python on Airflow, bringing commercial and open data sources together
• API layer: Node.js TypeScript app
• Databases and storage: MongoDB, S3/Athena, and Redis
• Deployment: AWS via Kubernetes on EKS using Terraform
• Most engineers are in the on-call rotation
• We sponsor OpenStreetMaps, MapLibre, and OpenAddresses

How We Use AI

• Engineers choose their AI tools; Claude and Codex are most popular
• We're actively building Claude skills, including teaching it how to debug HorizonDB
• All code changes are reviewed by an engineer knowledgeable in that area; Claude and Codex also review all PRs
• There is a range of AI usage; most engineers use it daily if not weekly
• We are excited about AI but don't compromise our coding standards

The Hiring Process

• Initial call with our Technical Recruiter
• Several technical Zoom calls with engineering team members: code screen, coding round, and system design round
• Final round interview at our NYC HQ, where you'll meet a co-founder, someone from outside engineering, and more people from Radar to go deeper into how we work

What You'll Do

• Own the data foundation under the geocoder including how location data is modeled, kept consistent, and served reliably, working across Scala, Python, and Rust
• Build the pipelines that bring many commercial and open data sources together, expanding coverage and quality across US and international data
• Help bring LLMs and agents into the data layer for enrichment, labeling, and quality, with the guardrails to keep them trustworthy
• Range across the geocoding stack when the work calls for it, from the serving path in HorizonDB to the Node.js/TypeScript API
• Have your work power over 1 billion API calls per day
• Talk to Radar customers and prospects, hear their feedback, incorporate it into your work and make them successful

You Should

• Think of yourself as a generalist engineer first, not tied to any particular stack
• Be interested in talking to customers or prospects and making them successful
• Be deeply curious about how things work, and have the tenacity to sit with hard problems and power through them

Bonus Points

• You are a former technical co-founder
• Have worked on a high throughput, high growth SaaS application
• Have worked on geospatial infrastructure
• Have built large-scale data pipelines or data-integration systems
• Have used LLMs in a data or ML pipeline (enrichment, labeling, or evaluation)

You'll Work With

• Tim Julien, CTO
• Rishant Dwivedi, Engineering Manager
• Our customers and prospects
• Our Customer Success, Sales Engineering, and Sales teams

Pay

Compensation Range: $200K - $300K

Benefits

• Competitive salary
• Meaningful stock options in a fast-growing company
• 401(k) plan with 4% match
• New HQ in Flatiron, NYC
• Top-notch equipment
• Catered lunches
• Unlimited PTO
• Health, dental, and vision insurance with 100% coverage for employees
• 12 weeks of paid parental leave
• Commuter and fitness benefits