Vetted MongoDB Professionals

“Worked on an AWS DynamoDB Journal team project building internal operator dashboards end-to-end, creating Java/Spring Boot APIs and integrating them into a Spring Boot/Thymeleaf/JavaScript UI to speed up debugging workflows. Has experience with data-heavy web apps and performance techniques (load balancing, caching, pagination, compression) plus hands-on debugging across unit/integration/E2E tests; also maintained and enhanced a React website at Global Spark.”

“Google Health engineer who owned and shipped an AI-powered clinical insights dashboard and NLP clinical note extraction service end-to-end (React/Next.js frontend; Python/Node microservices on GKE; TensorFlow transformers; BigQuery analytics). Demonstrated strong production rigor (CI/CD, testing, observability, guardrails for sensitive data) and delivered measurable outcomes including 30% faster diagnostics, 40% less manual documentation, 15% higher adoption, and 25% lower ops costs.”

“ML/NLP engineer with experience at NVIDIA and Cruise building production-grade AI systems across genomics/biomedical research and autonomous vehicle data. Has delivered multimodal LLM pipelines, large-scale entity resolution, and hybrid semantic search (BERT embeddings + FAISS + Elasticsearch), with measurable impact (≈40% accuracy/retrieval gains; ≈30% data consistency improvement) and strong MLOps practices (Kubernetes, CI/CD, MLflow, Prometheus/Grafana).”

Vernon Quan

Screened

Senior Full-Stack Software Engineer specializing in TypeScript, React, and Node.js

Menlo Park, CA7y exp

“Meta engineer who owned a heavily used internal goals/performance management feature end-to-end, driving major responsiveness improvements by restructuring frontend data loading and adding backend caching (Memcached), cache warmups, and query/index tuning. Strong focus on production quality: observability, error monitoring, and improving test coverage to prevent regressions during peak review cycles.”

“Backend/data engineer with production experience at Uber building a near real-time driver rewards service on AWS (FastAPI, PostgreSQL, Redis) with strong reliability and concurrency controls. Also delivered AWS Lambda/ECS containerized deployments with GitHub Actions CI/CD and cost governance, built AWS Glue ETL with schema-evolution handling, and drove a ~10x SQL performance improvement while owning incident response via CloudWatch.”

“NVIDIA engineer who built and shipped a production LLM-powered enterprise knowledge system (summarization, transcription, and Q&A) that cut document retrieval time ~30%. Deep hands-on experience with RAG (FAISS/Pinecone), GPU-accelerated microservices on AWS, and reliability/safety practices (Guardrails AI, prompt A/B testing, canary releases) plus strong MLOps orchestration across Airflow, Step Functions, and Kubernetes GitOps.”

Chang Qian

Screened

Senior Backend/Infrastructure Engineer specializing in large-scale integrity and content systems

Menlo Park, CA10y exp

“Backend/platform engineer who built Bilibili’s "Avalon" content moderation platform from a vague CEO mandate into a company-wide service (Go, gRPC, Kafka), including on-call, metrics, transparency tools, and multi-site resiliency work. More recently at Meta, scaled a high-traffic mistake-prevention platform by introducing capacity levers (prefiltering, caching, log sampling, fanout limits) and navigating org-wide constraints, including debugging a rule-engine threading bottleneck.”