Vetted Integration Testing 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.”

“Engineering manager/player-coach in the Alexa media ecosystem who led delivery of a Tier-1 gateway service enabling third-party providers (e.g., Spotify/Pandora) to control playback across users’ Echo devices, driving 10–15% lifts in engagement metrics. Deep in API design, AWS infrastructure choices (EC2 vs Fargate), OAuth/LWA auth flows, and production rigor (security reviews, load testing, feature-gated dial-ups), with demonstrated incident ownership and operational automation wins.”

“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.”

“LLM/agentic systems practitioner who partners directly with customers to productionize prototypes end-to-end—defining business-aligned metrics, building evaluation datasets, and shipping monitored, cost-bounded inference APIs on AWS Lambda. Notably delivered a vehicle damage classification system that cut manual review by 40% and stabilized agent workflows by instrumenting state transitions to uncover and fix a race-condition-driven skipped tool call.”

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.”

“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.”

Chavez Yi Wei Cheong

Screened

Mid-level analyst and software engineer specializing in AI, distributed systems, and product delivery

San Francisco, CA5y exp

“Engineer with end-to-end shipping experience spanning large-scale infrastructure at Meta and scrappy startup automation work. Built a C++ streaming platform for Facebook Marketplace with canary and chaos testing, and also created Selenium-based scraping and GTM automation workflows under ambiguous, real-world conditions.”

“Backend/AI engineer currently at Stripe building Minions, an internal LLM-based developer agent that automates code generation, bug fixes, and PR creation. They combine strong production LLM architecture skills with reliability engineering, having improved routine PR merge times by ~40-45%, lowered post-merge bug rates by 12%, and previously built an invoice-processing pipeline that achieved 91% straight-through processing in a B2B payments context.”