Vetted REST APIs Professionals

“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).”

“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.”

“Solutions Associate / technical support professional with experience assessing and fixing multi-script JavaScript issues, providing timelines, and managing scope changes with customers. Has supported customers by diagnosing recurring campaign issues, running technical demos with stakeholder feedback loops, and enabling self-service so customers can resolve problems independently.”

“AI/ML engineer who led Impacter AI’s production deployment of a specialized outreach LLM (CharmedLLM) fine-tuned on GPT-4.1, cutting API costs ~40% while boosting outreach effectiveness ~60%. Built the supporting MLOps and data infrastructure (MLflow, Kubernetes, PySpark, Kafka) and has agentic AI experience from University of Dayton, using LangChain + RAG and vector search (Pinecone) to improve reliability and reduce hallucinations.”

“Frontend engineer who has led end-to-end delivery of a climate-risk visualization/financial impact web platform using micro-frontends (Webpack Module Federation), a shared MUI design system, and React Query server-state to keep independent modules consistent and performant. Also improved a complex rules-heavy document editor (Crove.app) by eliminating input lag with memoization + Web Workers and introducing a headless rendering engine reused across products, with disciplined rollout via feature flags and Sentry monitoring.”

“Built production automations and LLM/RAG prototypes spanning enterprise and personal use cases: cleaned a 5TB Akamai storage estate via n8n + legacy REST APIs (20–25% deletion, cost savings) and developed an internal Qdrant-backed RAG chatbot evaluated with automated scoring plus user feedback. Also prototypes latency-sensitive agentic tools (e.g., automated hotline calling) and designs guardrails against prompt injection for email/PDF processing workflows.”