Vetted Backend Development Professionals

“Full-stack engineer with early-stage startup experience who shipped and owned production Next.js (App Router + TypeScript) features end-to-end, including auth-aware APIs, caching, and post-launch monitoring/iteration. Demonstrates strong performance and reliability chops across React UX optimization, Postgres analytics modeling/query tuning (validated via query plans), and durable ingestion workflows with retries/idempotency.”

“QA engineer with Citibank experience owning mobile automation and cross-platform validation (Android/iOS), including push notifications, RBAC, and backend API/data sync checks. Demonstrates strong Cypress/JavaScript E2E expertise—stabilizing CI-flaky React tests via cy.intercept—and builds pragmatic GitLab CI pipelines with smoke/regression gating plus rich reporting (Cypress Dashboard, Slack).”

“Built a healthcare app backend and supporting product pieces from scratch for Maverick Health—covering database schema, API structure, Node.js implementation, and UI design in Figma—while targeting 10,000 patients and keeping AWS run costs to ~$20–$30/month. Shipped an Android closed beta on Google Play and handled real-world launch hurdles like privacy policy compliance and push notification infrastructure.”

“Built and shipped a production RAG-based enterprise knowledge assistant to replace slow/inaccurate search across millions of documents, using LangChain orchestration with GPT-4/LLaMA and vector databases. Strong focus on production constraints—latency, hallucination control, and cost—using hybrid retrieval, guardrails, LLM-as-judge validation, and model routing, and has experience translating non-technical stakeholder pain points into measurable outcomes.”

“Full-stack engineer and ML assistant in UC Irvine’s CS department who deployed a lab project showcase platform and integrated on-demand execution of computational projects using Docker for isolation. Also built and optimized Linux cloud/cluster test automation for research, diagnosing RAM and network sync bottlenecks, and later led development of a Python-based predictive analytics tool for musicians using probabilistic graphical models and flexible data pipelines.”

“Backend engineer from Emphasis who modernized legacy, tightly coupled workflow systems into observable, event-driven microservices using Kafka. Led a monolith-to-microservices refactor with shadow traffic, feature flags, canary rollout, dual writes, and reconciliation, and strengthened reliability with idempotent consumers, DLQ/replay, and an outbox pattern to prevent DB/event inconsistency. Strong focus on secure multi-tenant APIs (OIDC/JWT, RBAC/ABAC, Supabase-style RLS) and frontend enablement via OpenAPI and typed client generation.”

“LLM-focused engineer who has shipped multiple production-grade AI reliability systems: an LLM output validation/monitoring service (FastAPI) with prompt versioning and failure analytics, plus a RAG feature using embeddings/vector DBs with retrieval thresholds, schema/context validation, and safe fallbacks. Strong in evaluation loops (groundedness, schema accuracy, human review) and scalable pipelines for messy document ingestion with observability and early detection of data quality issues.”

“Capgemini engineer with hands-on ownership of production TypeScript backend integrations and loyalty-platform modernization. Built AWS event-driven microservices (SNS/SQS/Lambda) with GraphQL vendor calls and DynamoDB persistence, emphasizing reliability patterns like retries and idempotency; reports ~25% response-time improvement after migrating/optimizing services and workflows.”

“Lead hardware/integration engineer on a high-speed autonomous drone for adversarial drone tracking and surveillance, owning the full stack from custom electronics and flight-controller tuning to ROS2 SLAM and GPU-accelerated computer vision. Built a custom USB-based ROS2 LiDAR driver and migrated SLAM from SLAM Toolbox to Google Cartographer, while boosting YOLOv5 tracking from ~2 FPS to ~45 FPS on an NVIDIA Jetson through CUDA/dependency optimization.”

“Product-minded full-stack engineer from CouponDunia who owned end-to-end notification and recommendation services at million-user scale. Built internal admin/analytics and operations dashboards in React/TypeScript with typed contracts and scalable Node.js REST APIs, and has deep microservices experience with Kafka/RabbitMQ (idempotency, retries/DLQs, partitioning, consumer tuning, and observability).”

“Backend engineer from Optum who built and optimized a real-time, Kafka-driven healthcare claims processing platform handling 1M+ claims/month. Strong in reliability, state management, and observability for distributed systems, plus production deployment automation with Docker/Kubernetes and CI/CD; no direct ROS/robotics simulator experience yet but frames work in robotics-adjacent real-time principles.”

“Designed and deployed a production LLM agent platform at the National Institutes of Health to reduce time spent searching fragmented internal documentation, combining RAG grounding with multi-step tool-calling workflows and integration into legacy services via inference APIs. Emphasizes production-grade reliability through automated evaluation on real queries, guardrails/safe-failure behaviors, and ongoing A/B testing and monitoring, and has experience translating non-technical stakeholder goals into measurable success metrics.”

“Backend/data engineer with hands-on production experience across FastAPI microservices and AWS data platforms. Has delivered serverless and Glue/EMR-based ETL pipelines with strong observability (Prometheus/Grafana/Sentry, CloudWatch/SNS), schema-evolution resilience, and measurable SQL performance wins (5 min to <30 sec). Open to onsite meetings in the Bethesda, MD area and flexible on remote arrangements.”

“Backend/ML engineer who built an end-to-end greenwashing detection system for corporate ESG reports: Python preprocessing pipeline, logistic regression + fine-tuned DistilBERT models, and a Dockerized FastAPI inference service optimized for latency. Internship experience maintaining GitLab CI/CD for TypeScript services (Jest/Playwright), improving pipeline stability and test determinism; familiar with Kubernetes/GitOps concepts and AWS CLI/SSO.”

“Backend Python engineer who owned an AI-driven healthcare staffing matching service, rebuilding the model inference/data pipeline to eliminate blocking bottlenecks and cutting API latency by ~33%. Experienced running Python services on Kubernetes with GitOps/ArgoCD, and has executed a cloud-to-on-prem rollout under tight resource and tooling constraints while also building event-driven streaming updates via a message broker.”

“ML/NLP practitioner with banking experience (M&T Bank) who has built a GPT-4 RAG system using LangChain and Pinecone to connect unstructured customer data with internal knowledge bases, improving accuracy and reducing manual lookup time by 50%+. Strong in entity resolution and productionizing scalable Python data workflows, including major performance wins by migrating bottleneck joins from Pandas to Dask.”

“End-to-end engineer who has productionized AI automation and RAG capabilities, building full-stack systems (React/Node/Redis/Postgres + vector DB) with evaluation-driven quality gates and monitoring. Reported ~60% reduction in manual ops time and major turnaround improvements, and has experience modernizing legacy systems safely via feature flags and parallel runs while working across product, data, and ops teams (System1).”

“Full-stack engineer who led an end-to-end rebuild of a service-agent case management app (React SPA + backend/DB updates) and added Datadog monitoring, improving agent throughput by ~1 case/hour and saving roughly $15K/month. Experienced in incremental legacy modernization (including moving a legacy React frontend toward a Rails-based approach) with heavy unit/E2E testing and strong cross-team stakeholder communication.”