Teams at Raydar

Own full-stack engineering work from scoping through release and refinement. Automate manual application processes, build AI components that analyze complex data, and deliver user-facing interfaces and internal utilities across frontend and backend systems. Investigate relevant rules and standards, incorporate user feedback, and collaborate across the company. The role requires experience shipping features for live products and managing ideas through production, with bonus experience in AI pipelines, task runners, model evaluation, GIS, and geospatial data.

Owns cloud infrastructure and deployment pipelines as the sole infrastructure engineer for a small product team. Responsibilities include CI/CD, AWS architecture, security controls, infrastructure as code, monitoring, incident readiness, networking, cost optimization, vulnerability management, and customer security reviews. The role requires independently building and operating reliable production systems across development, staging, and production environments.

Lead AI agent quality measurement, evaluation design, error analysis, and reliability improvements. Build backend infrastructure and services that run, evaluate, and monitor agents at scale. Investigate agent failures, implement platform-level fixes, shape the AI platform quality roadmap, and mentor engineers on evaluation rigor and error analysis.