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Vetted Google Cloud Platform Professionals
Pre-screened and vetted.
Mid-level Business Analyst specializing in supply chain analytics
Mid-level Software Engineer specializing in Python automation and GenAI on AWS
Junior Machine Learning Engineer specializing in Generative AI and LLM agents
Mid-level Frontend Engineer specializing in React/Next.js and blockchain products
Junior Full-Stack Developer specializing in AI integrations and LLM research
Mid-Level Full-Stack Software Engineer specializing in cloud microservices and Voice AI
Mid-level AI/ML Research Engineer specializing in NLP, LLM agents, and multimodal systems
Mid-level AI/ML Engineer specializing in GenAI, agentic AI, and RAG pipelines
Junior Full-Stack Developer specializing in Django/React and cloud-native APIs
Mid-level Full-Stack AI Engineer specializing in agentic AI and RAG systems
Mid-level Frontend Engineer specializing in SaaS, FinTech, and cloud security
Mid-level Software Engineer specializing in full-stack web, UX, and AI-assisted products
Entry-level AI/ML Engineer specializing in RAG and conversational AI
Billy Kipkorir Bett
Mid-Level Full-Stack Software Engineer specializing in Web3 and AI-enabled SaaS
“Frontend engineer who has led end-to-end builds across both Web3 gaming (Next.js app deployed on Telegram) and a sensitive, data-heavy mental health NGO dashboard. Experienced implementing scalable frontend architecture and strict code-quality workflows, plus shipping complex NFT/blockchain pipelines (AI generation → contract deployment → wallet/payment flows) validated on testnets with staged rollout and monitoring.”
Umair Shamoon
Mid-level Full-Stack Developer specializing in MERN/MEAN and cloud-native web apps
“Frontend engineer with end-to-end ownership of React/Next.js products, focused on scalable component-based architecture and quality via CI/CD, automated testing, and disciplined PR reviews. Built React + TypeScript dashboards with role-based views using Zustand, and improved existing codebases by decoupling components and boosting performance through code splitting, lazy loading, and standardized shared components.”
Gabe Hoing
Intern-level software engineer specializing in full-stack and data systems
“Built an AI agent management system in a senior design project to support cybersecurity analysts with gathering and triaging emerging threat intelligence from sources like CISA. Stands out for a thoughtful, production-minded approach to AI development, using specialized agents, strict output schemas, and deterministic controls to manage failure cases.”
“Full-stack AI engineer who has built and deployed multiple end-to-end LLM products, including an AI interview assistant, a multi-agent market research platform, and a policy document explainer. Particularly strong in productionizing agentic workflows, integrating tools like Whisper, Tavus, LiveKit, CrewAI, and LangGraph, and hardening messy real-world AI/document pipelines with validation, memory isolation, and fallback handling.”
Lalith Kambala
Junior Full-Stack Engineer specializing in AI-powered web applications
“Full-stack product engineer who has shipped AI-powered job board moderation and validation features end to end across React/TypeScript, serverless backends, and Postgres. Stands out for combining UX polish, LLM-backed workflow design, and reusable async infrastructure patterns to improve reliability, speed of delivery, and user participation.”
Mahaboob Johny
Mid-level Data Analyst specializing in SQL/Python analytics, ETL pipelines, and BI dashboards
“Data/AI practitioner who built a production LLM-driven healthcare claims analytics and dashboarding system to reduce avoidable ER visits—processing 1.4M+ claims, flagging 19% as non-emergent, and projecting ~$2.8M in annual savings. Demonstrates strong real-world LLM reliability and performance engineering (grounding, numeric validation, caching, materialized views, quantization) plus orchestration experience with Airflow and Azure Data Factory.”