Vetted Google Cloud Platform Professionals

Affan Ahmed

Screened ReferencesModerate rec.

Senior Full-Stack & Machine Learning Engineer specializing in scalable SaaS and cloud AI

Remote, Pakistan7y exp

“Frontend engineer who led an enterprise self-serve analytics dashboard end-to-end using a micro-frontend React/TypeScript architecture with strong integration discipline (contracts, CI gates, ADRs). Demonstrated measurable performance wins (35% faster LCP) through code splitting, lazy loading, and tighter Redux subscriptions, and uses feature flags plus automated E2E coverage for controlled rollouts.”

“Built and shipped a production LLM hallucination detection and monitoring pipeline using semantic-level entropy (embedding-clustered multi-generation variance) to flag unreliable outputs in downstream automation. Implemented a scalable async architecture (FastAPI + Docker + Redis/Celery) with strong observability (structured logs + PostgreSQL) and developed evaluation loops combining controlled prompts and human review; also partnered with non-technical stakeholders on AI-driven form validation/document processing.”

“AI engineer who built an agentic, production-deployed LLM workflow for tobacco violation parsing and automated multi-case creation, using six specialized agents and a human-in-the-loop confidence-threshold routing design. Addressed data privacy constraints by generating synthetic datasets with LLM prompting, and orchestrated reproducible end-to-end pipelines in LangChain with robust testing and evaluation (precision/recall, micro-F1).”

“Backend-focused engineer with experience spanning research and healthcare: owned a Python/SQL data pipeline that transformed vulnerability-fix code data from SQLite into model-ready JSON for LLM analysis. Also deployed Dockerized Spring Boot microservices to Kubernetes with Jenkins CI/CD and built Kafka-based real-time event streaming (appointment/report events) with idempotent consumers to avoid duplicate processing.”

“Backend/platform engineer who built an LLM-driven QA automation system (“mockmouse”) using a Flask orchestration microservice, Socket.IO real-time updates, Redis caching, and strict Pydantic schemas to turn prompts into reliable action graphs and automated browser tests. Has hands-on Kubernetes delivery experience (Docker/Helm/Jenkins) and has supported large migration programs, validating ETL cutovers with 1M+ synthetic records and rigorous output comparisons; also built event-driven monitoring/anomaly detection streaming into Grafana.”

“Backend/AI engineer with production experience in legal tech: built a high-scale licensing/subscription API (FastAPI/Postgres/Stripe) and shipped a RAG-based chatbot for an eDiscovery platform. Designed a robust legal document ingestion workflow that processes thousands of documents into a searchable vector index with clear retry/escalation logic, and has demonstrated measurable Postgres performance wins (200ms to 10ms) using EXPLAIN ANALYZE and composite indexing.”

David Pang

Screened

Intern Full-Stack Software Engineer specializing in web apps and healthcare APIs

1y exp

“Full-stack developer who built an end-to-end e-commerce application with admin/blog/announcement features using Node/Express and AWS S3, emphasizing security via expiring presigned URLs. Also has strong distributed-systems fundamentals from implementing the Raft consensus algorithm (replication logs, majority acks, leader elections) and has created build automation tools (GNU Makefiles/scripts) to streamline team workflows.”

Akash Mishra

Screened

Mid-level Data Engineer specializing in ETL pipelines on GCP

Miami, Florida5y exp

“Full-stack engineer from Larix Technologies who led a Next.js migration feature: an internal real-time workflow status dashboard built with App Router/TypeScript using server components for initial render and client polling for live updates. Demonstrates strong post-launch ownership—monitoring latency/error rates, adding caching and payload reductions, and optimizing Postgres queries/indexes—plus experience building durable RabbitMQ-based message routing workflows with idempotency, retries, and dead-letter queues.”

Shehab mohamed mohamed

Screened

Junior AI Engineer specializing in MLOps, LLMs, and multi-agent systems

Cairo, Egypt2y exp

“ML/AI engineer focused on production-grade systems, with experience building a low-latency multi-agent 'neural concierge' booking platform used across domains like restaurants and hospitals. Also worked on a healthcare computer vision system for nystagmus/eye-movement analysis, showing a mix of scalable LLM infrastructure, MLOps, and safety-conscious medical AI experience.”