Vetted Git Professionals

“Frontend engineer who led a networking-device simulation PoC into a production-integrated product, designing microservice-style containerized architecture and optimizing massive telemetry streams with WebSockets and Kubernetes-based scaling. Built a React+TypeScript network orchestration dashboard (Platina Command Center) and drove quality/performance through unit/E2E testing with measurable browser/API performance metrics and CI/CD automation for rapid monthly releases.”

“Built an end-to-end mobile + web Q&A marketplace connecting users with professionals, including real-time chat and Stripe-based monetization (products/subscriptions). Hands-on with scaling Firebase/Firestore (subcollections, composite indexing, pagination) and mobile caching/sync challenges. Also created an internal AI-driven report generator that turned chatbot outputs into curated graphs and PDFs for marketing, iterating based on stakeholder feedback.”

“Full-stack engineer with deep AWS serverless and reliability experience in fintech/underwriting systems, including eligibility scoring and dynamic rule deployments. Built and productionized an LLM-powered incident RCA assistant (Bedrock Claude 3 + custom RAG + React) achieving 92% precision and ~75% MTTR reduction, with mature guardrails (evals, drift monitoring, HITL, audit logs) and strong operational rigor (canaries, chaos testing, DLQ remediation).”

“Robotics Support Engineer at HAI Robotics supporting a 385-robot warehouse fleet at a Shein client site. Built a production automation and reporting workflow to diagnose and resolve abnormal shelf locations, cutting incidents from ~250/day to ~25/day while providing actionable root-cause data to client/ops/maintenance. Hands-on ROS 2 (Humble) debugging across Nav2/localization/TF and sensor integration issues including QoS and firmware coordination.”

“Frontend engineer focused on scalable architecture and long-term maintainability, emphasizing modular component design in React + TypeScript. Has experience building reusable component libraries (including Storybook and shared repos) and collaborating with design/product to refine UX workflows, reducing development time over successive iterations.”

“QA automation engineer in a banking domain who owned an end-to-end automation suite for critical money movement flows (onboarding, funding, transfers). Demonstrated impact through edge-case coverage (min balance, boundary amounts, repeated actions, timeouts), CI/CD gating with smoke vs regression suites, and catching a high-impact timing defect where UI success masked incorrect balance updates.”

“Full-stack/backend engineer who owned end-to-end delivery for DentalScan, an AI-powered healthcare platform, building Kafka-based Node.js microservices plus Next.js clinician dashboards and CI/CD on Vercel. Productionized LLM/voice AI patient communication (Twilio/Retell AI) with prompt templates, guardrails, and monitoring, supporting 1,000+ scans/day at sub-100ms latency and reducing clinic admin workload. Previously modernized an agricultural data platform at Infosys to Spring Boot/Docker microservices with Redis, Jenkins CI/CD, and AWS CloudWatch monitoring.”

“Frontend engineer (Teradata) who led an enterprise analytics dashboard end-to-end, building complex React + TypeScript interfaces with near-real-time updates and large data volumes. Strong track record in scalable frontend architecture, performance tuning (render optimization, payload reduction), and quality at speed via CI/CD, automated regression testing, and incremental rollouts in an Agile environment.”

“Engineering leader who delivered a Magento-to-Shopify rebuild ahead of schedule while maintaining 100% team retention over 4 years at Hydrobuilder Holdings. Also built and ran a concert-listing platform (TourVolume) in production for 12+ years (Webby Honorable Mention) and later open-sourced the full codebase. Deep experience in auth/API platforms on AWS, including moving critical auth services from Lambda to ECS to eliminate cold-start latency.”

“Built and deployed a production LLM-powered university support chatbot on Azure using a RAG pipeline, focusing on reducing hallucinations, improving latency, and handling ambiguous queries via confidence checks and clarification prompts. Also has hands-on orchestration experience (Airflow/Azure Data Factory), including hardening a demand-forecasting ingestion workflow with sensors, retries, and automated alerts, and uses a metrics-driven testing/monitoring approach for reliable AI agents.”