Vetted Unit Testing Professionals

“Frontend engineer focused on scalable React + TypeScript architecture and design-system style reusability, with demonstrated refactoring impact in legacy codebases. Delivered a high-visibility, filterable “Project Showcase” feature in 3 weeks (CMS-integrated, responsive, CI/unit-tested) and has implemented real-time UI updates via WebSockets for chat profile presence.”

“Frontend/full-stack engineer who built a fast-food ordering web app and a minimal one-page real-time admin dashboard (Supabase + Postgres) with role-based access. Emphasizes scalable architecture, strict TypeScript validation, and quality practices (error boundaries, backend validation, unit testing), and has experience refactoring messy codebases into reusable components with consistent Tailwind theming.”

“Built FlowPilot, an AI-powered product that generates complete importable n8n workflows from natural-language prompts using a RAG pipeline (Qdrant + LangChain) and a multi-stage agent with a scoring/repair 'Judge' loop for intent alignment. Experienced in backend architecture across Laravel/Node microservices and production AI/RAG systems, plus performance debugging from async job offloading to database index tuning after ORM migrations.”

“Backend/infrastructure engineer in the EBS org focused on global server lifecycle and fleet reliability. Led a major modernization from manual, ticket-driven recovery to centralized Python services and operator tooling with DynamoDB-backed state, strong auth/allowlisting, and CloudWatch monitoring, plus an AWS Glue/S3/SNS data pipeline to join server and hardware datasets for global operational querying and automated recovery.”

“Built and deployed an LLM-powered financial document processing and summarization platform at Morgan Stanley using a production RAG pipeline (PDF ingestion, embedding-based retrieval, schema-constrained JSON outputs) delivered via FastAPI microservices on Kubernetes. Drove measurable impact (40% reduction in manual review time) and improved factual accuracy for numeric fields by 30% through metadata-aware retrieval, strict schemas, and post-generation validation, with a human feedback loop from financial analysts.”