# Senior/Staff Software Engineer, Search  at Radar Labs

Radar Labs is hiring a Senior/Staff Software Engineer, Search  for a remote role open to applicants in United States. It pays $200k-$300k a year and Level rates it Builds AI ●●●●; you can [apply on Radar Labs](https://jobsbylevel.com/go/d90e7663-ce20-4412-8649-0bb62204d3bb?utm_medium=ai-agent).

AI Level 4, AI centrality 85 out of 100. Remote (New York ; US Remote).

## Details

- Company: [Radar Labs](https://jobsbylevel.com/companies/radar-labs)
- AI level: AI Level 4 (score 85 out of 100)
- Location: Remote (New York ; US Remote)
- Salary: $200k-$300k
- Posted: October 22, 2026
- Apply: https://jobsbylevel.com/go/d90e7663-ce20-4412-8649-0bb62204d3bb?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=senior-staff-software-engineer-search-at-radar-labs-99d6c6

## Prepare for this job

The job page lists 4 likely interview questions for this offer, with a CV checklist: https://jobsbylevel.com/jobs/senior-staff-software-engineer-search-at-radar-labs-99d6c6

## Description

About Radar Radar is the global leader in geolocation, with geofencing SDKs, maps APIs, and AI-enabled solutions for marketing, fraud, and operations teams. Why is Radar the best place to work? We're trusted by some of the world's best companies, from high-growth startups to the Fortune 500. We have incredible scale: We're processing over 1 billion API calls per day from hundreds of millions of devices. We're well-resourced, and 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. We were recently named a top 10 best place to work in NYC by Crain's. Despite our growth and scale, we're still just getting started. That's where you come in. About the role: We're looking for a Senior/Staff Software Engineer, Search to improve the data and search systems behind Radar's geocoding platform. Our daily traffic is over 1 Billion API calls / day (15,000 requests / second), so you will be operating at scale. You'll improve the quality and coverage of our location data, build and automate the pipelines that keep it growing, and improve how we understand queries, retrieve candidates, and rank results across geocoding and autocomplete. You'll use ML and LLMs where they can materially improve these systems, from data enrichment and matching to query understanding and search relevance. This is a software engineering role first, you don't need a research background, but you should be excited to work across data, search, and backend systems and reach for ML when it's the right tool. This role will be based out of 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 at Radar fit one of two molds, technically: either Staff level expertise in one stack, or "Multi-Stack" at any level. We say "Multi-Stack" because "Full-Stack" has the connotation of "Frontend and Backend", but Radar Engineers might also work on Mobile or Data engineering. Not that you need to be an expert in all of those, but a desire to learn, jump around to different stacks, and get things done is the important part. We care a lot about shipping fast and talking to customers. We're committed to our product vision of full-stack location infrastructure, but we also know that customer feedback is a treasure map to gold. Even though Slack is the brain of our company, working together in-person in our NYC HQ is the fastest way for us to get things done. We meet on Mondays to plan out work for the week in small groups and use Linear for planning. To us, a week is a long time, and we expect to ship big things every week. The stack: Our core backend service is HorizonDB, a geospatial database written in Rust that powers geocoding: forward and reverse geocoding, autocomplete, and address validation. It's built on custom search indexes and stores like Tantivy, RocksDB, and FSTs, with ML models for query understanding and ranking. Our geospatial data pipelines are written in Scala and Python on Airflow, merging commercial and open data sources into the indexes HorizonDB serves. The API layer is a Node.js TypeScript app, and we use MongoDB, S3/Athena, and Redis. Everything is deployed to 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 what AI tools they use, Claude and Codex being the most popular. We're actively building Claude skills - for example we've taught it how to debug HorizonDB, our geospatial database. All code changes are reviewed by an Engineer knowledgeable in that area. Claude and Codex also review all PRs. There is a range of how much engineers use AI. Most use it daily if not weekly. We are excited about what AI can do, but we also recognize the

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Source: https://jobsbylevel.com/jobs/senior-staff-software-engineer-search-at-radar-labs-99d6c6

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