Vetted GraphQL 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.”

“Front-end engineer with strong experience building high-performance browser UIs for financial professionals, especially complex onboarding flows and real-time data dashboards in React. Stands out for combining browser-level performance tuning, asynchronous architecture expertise, and measurable business impact, including 30% faster onboarding and 15% higher client satisfaction; also brings Angular/C#/D3 experience from higher-ed analytics platforms.”

“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.”

Sai Kumar K

Screened

Mid-Level Frontend Engineer specializing in legal data platforms

5y exp

“Built and operated end-to-end legal-document data pipelines fed by hundreds of scraper sources, emphasizing data quality validation, reliability (CloudWatch monitoring/alerting, retries, backfills), and serving enriched legal data via serverless AWS APIs (Lambda/API Gateway). Experienced in keeping API contracts stable with additive versioning practices and shipping MVPs quickly with CI/CD and observability in place.”

Tarun Gowda

Screened

Mid-level AI Engineer specializing in Generative AI and multimodal RAG

Morristown, NJ3y exp

“Full-stack engineer who helped build and launch an internal genAI platform called GAIL, supporting multiple LLMs, confidential document upload for RAG pipelines, and collaborative chat. Worked across FastAPI, React/TypeScript, AWS/DynamoDB, and Azure, with notable ownership of backend RAG logic, MCP integration architecture, and frontend fixes that improved chat usability.”

“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.”

“Data engineer with ~4 years of experience building Python-based data ingestion/processing services and real-time streaming pipelines (Kafka/PubSub + Spark Structured Streaming). Has deployed containerized data applications on Kubernetes with GitLab CI/Jenkins pipelines and applied GitOps to cut deployment time ~40% while reducing config drift. Also supported a legacy on-prem data warehouse/backend migration to GCP using phased migration and parallel validation to meet strict reliability/SLA needs.”