RADAR is an AI-powered retail intelligence platform that combines proprietary overhead sensors, software, and analytics to deliver real-time, item-level inventory visibility.
About Radar Radar https://radar.com 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 Site Reliability Engineers to work on our production infrastructure. Radar is a high-throughput, data intensive application handling 1 billion+ API calls per day. Over the past year, Radar has been used from over 100M devices worldwide. We run a multi-availability zone architecture and a major initiative is to enhance our deployment to be multi-region. The stack: We use Terraform to manage our infrastructure. We deploy everything to AWS via EKS. We use MongoDB deployed to Atlas. We do CI and deployments via CircleCI. We monitor production with CloudWatch, grafana, Pingdom and PagerDuty. DNS is managed by CloudFlare. Most engineers are in the on-call rotation. Our main server languages are TypeScript and Rust. Our data pipelines are written in Airflow and Scala Spark. We sponsor OpenStreetMaps, MapLibre and OpenAddresses. How we use AI: - Engineers choose what AI tools they use, Claude 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 Copilot 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 risks and don't compromise our coding standards. 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. All projects are run by an Engineering lead, an executive and a Go-to-Market lead. Engineers figure out what to build, talk to customers, talk to prospects, help close them, get them live and make them successful. One of the hardest and most valuable practices we have is Walk A Mile - which is shorthand for putting yourself in the user's shoes - but also for literally walking a mile and dogfooding the Radar SDK, because you can't create location infrastructure behind a desk - you have see how the device behaves in the real world. To us, a week is a long time, and we expect to ship big things every week. How we use AI: - Engineers choose what AI tools they use, Claude and Cursor being the two most popular. - All code changes are reviewed by an Engineer knowledgeable in that area. Cursor and CoPilot also review all PRs. - There is a range of how much engineers use AI. Some use it heavily, others less so. - We are excited about what AI can do, but we also recognize the risks and don't compromise our coding standards. The hiring process: After a call with our Technical Recruiter, you'll do several technical Zoom calls with members of our engineering team: code screen, coding round, and system design round. If those go well we'll invite you to our NYC HQ for a final round interview. You'll meet one of our co-founders, someone from outside engineering, and meet more people from Radar. We'll go into more depth about how we work to see if there is a match. What you’ll do: - Work on core Radar infrastructure using Terraform all deployed to AWS via EKS - Work on critical company-level initiatives, for example, 99.99+% availability, multi-region deployment, and cloud cost-saving activities - Have your work be used by 100's of millions of devices - Be part of the on-call rotation (one week rotation every 1-2 months) - Talk to Radar customers and prospects, hear their feedback, incorporate it into your work and make them successful You should: - Have experience managing a production AWS environment via Terraform - Have experience with high availability multi-region production infrastructure running on Kubernetes - Have experience managing large sharded Mongo clusters with heavy read-write workloads - Have experience at a high growth startup - Be interested in talking to customers or prospects and making them successful Bonus points if you: - Are a former technical co-founder - Have experience with high throughput data intensive applications You’ll work with - Tim Julien https://www.linkedin.com/in/timjulien/, CTO - Dai Shi https://www.linkedin.com/in/shidai/, Seni