Vetted JUnit Professionals

“Full-stack TypeScript engineer who has owned a real-time workflow/communication platform end-to-end in production (Node/TS + React, Postgres/Redis, Kafka, Docker/CI/CD). Demonstrates strong distributed-systems pragmatism—designing for failure with retries, DLQs, idempotency keys, and atomic writes—plus operational practices like structured logging, monitoring, and zero-downtime deployments.”

SAI PRASHANTH

Screened

Mid-level Full-Stack Software Engineer specializing in cloud-native microservices and FinTech

USA5y exp

“Software engineer/product-minded builder who owns customer-facing products end-to-end and ships in 1–2 week increments using CI/CD, automated testing, and feature flags. Built a TypeScript/React/Node platform that cut page load times by 40% and scaled to 3x concurrent users, and designed RabbitMQ-based microservices with Prometheus/Grafana monitoring. Also delivered an internal real-time support analytics dashboard that reduced response times by 30%.”

“Full-stack product engineer who has shipped customer-facing features end-to-end, including a product detail page backed by Java/Spring Boot microservices and a React/TypeScript UI. Demonstrated measurable impact through performance and maintainability improvements (30% faster APIs, 25% less duplicated UI code, 40% reduced API complexity via GraphQL) and has operated/scaled apps on AWS with CI/CD, monitoring, and incident-driven scaling fixes.”

“Lead developer on a Warner Brothers Discovery media management platform, building Python/Flask APIs and AWS-based workflows. Delivered a serverless search overhaul (Lambda + API Gateway + OpenSearch Serverless) while maintaining parity with legacy Rekognition tag-based search, and implemented event-driven ETL (SNS/SQS) to ingest/validate CSV metadata into PostgreSQL with strong logging and incident response practices.”

“Robotics software engineer focused on backend/integration for indoor autonomous mobile robots, with hands-on ROS 2 experience integrating Nav2/AMCL/TF2 and LiDAR/camera pipelines. Emphasizes production readiness—robust failure recovery, QoS-tuned distributed communication, and strong observability (logging/health checks)—validated through Gazebo simulation, sensor-data replay debugging, and Docker-based CI/CD deployment.”

“Backend engineer who owned and shipped a campaign analytics API (FastAPI/Postgres/Redis/Celery) with ingestion from Instagram/YouTube, JWT auth, tests, and Docker deployment; improved performance from >1s to <150ms using precomputed aggregates and composite indexes. Experienced with Kubernetes GitOps using GitHub Actions + ArgoCD (zero-downtime rollouts, one-click rollbacks), Prometheus/Grafana observability, hybrid cloud-to-on-prem migrations, and real-time notification streaming via Redis Pub/Sub + WebSockets.”