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Radar is the global leader in geolocation infrastructure, processing over 1 billion API calls per day from hundreds of millions of devices worldwide. The company has raised $85.5M from top-tier investors including Accel and Insight Partners and was recently named a top 10 best place to work in NYC by Crain's.
You will manage and grow a globally distributed Site Reliability Engineering team responsible for Radar's production infrastructure. Your core responsibilities include leading the team to ensure scalability and high availability of services worldwide, driving observability and incident management practices, and championing automation over manual processes.
The technical environment is sophisticated: infrastructure managed via Terraform deployed to AWS EKS, MongoDB on Atlas, CI/CD through CircleCI, monitoring via CloudWatch, Grafana, Pingdom, and PagerDuty. The platform handles massive scale with multi-availability zone architecture, and a major initiative is expanding to multi-region deployment. Server languages include TypeScript and Rust; data pipelines use Airflow and Scala Spark.
Key responsibilities: manage and mentor the SRE team; own observability, monitoring, and incident management; work on core infrastructure; partner with product, data, platform, and security teams; drive company-level initiatives like 99.99%+ availability, multi-region deployment, and cloud cost optimization; ensure compliance and security by default; participate in on-call rotation; engage with customers and prospects to understand their needs.
You should have experience managing production AWS environments via Terraform, building high-availability multi-region infrastructure on Kubernetes, managing large sharded MongoDB clusters with heavy read-write workloads, and working at high-growth startups. The role requires both hands-on technical depth and leadership capability—you'll dive into production issues while guiding team strategy. Customer engagement and dogfooding the product are core to Radar's culture. The team values shipping fast, learning across multiple technical stacks, and understanding real-world user behavior.
