.png){kind=logo}
Vetted Google Cloud Platform Professionals
Pre-screened and vetted.
Senior Software Engineer specializing in Java backend and OLAP systems for Ads platforms
Senior Full-Stack Software Engineer specializing in cloud-native web platforms and FinTech
Senior AI/ML Engineer specializing in LLM applications, RAG systems, and MLOps
Senior Software Engineer specializing in AI infrastructure and distributed systems
Staff Machine Learning Scientist specializing in NLP, LLMs, and Generative AI
Senior Software Engineer specializing in full-stack systems and ML-driven platforms
Staff AI/ML Engineer specializing in LLMs, fraud detection, and MLOps
Staff Software Engineer specializing in backend systems for healthcare and FinTech
Senior Data Engineer specializing in cloud data platforms and real-time streaming
Senior Backend Software Engineer specializing in cloud platforms and event-driven systems
Senior Full-Stack Software Engineer specializing in Mobile and AR/VR platforms
Staff Full-Stack Software Engineer specializing in cloud platforms and healthcare data pipelines
Senior Software Engineer specializing in backend, AI workflows, and distributed systems
Senior Software Engineer specializing in DevOps and CI/CD infrastructure reliability
Senior Full-Stack Software Engineer specializing in AI-powered distributed systems
Jesse Olson
Executive AI technology leader specializing in agentic AI and enterprise transformation
“Candidate is exploring a startup in the autonomous agentic AI space and is approaching it with a disciplined founder mindset. They are evaluating market opportunity, competition, customer pain, ROI, technical feasibility, and MVP options while already speaking with potential customers across verticals to validate needs and buying processes.”
Daozheng Chen
Staff Full-Stack AI Engineer specializing in FinTech and Enterprise SaaS
“Full-stack engineer with Yahoo Finance experience building AI-powered investment and analytics features. They combine modern TypeScript/React/NestJS development with strong backend systems skills in PostgreSQL, Redis, Kafka, and Kubernetes, and have driven architectural improvements from synchronous workflows to event-driven microservices in a high-traffic financial environment.”
Andrew Coven
Executive Software Engineering Leader specializing in AI/ML products and large-scale platforms
“Engineering leader who drove Lightroom Mobile’s roadmap at Adobe by enforcing reuse of Photoshop imaging tech to deliver RAW, non-destructive mobile editing with full Creative Cloud compatibility. In startup environments, has repeatedly scaled and professionalized engineering orgs (career ladders, evaluation systems, delivery process) and led high-stakes cloud/platform transformations—migrating off Heroku and consolidating fragmented AWS/GCP usage into a single GCP platform—improving reliability, deploy speed, and cutting cloud costs by 20%+.”
Danny Anop
Senior Full-Stack Engineer specializing in SaaS, e-commerce, and frontend platforms
“Frontend-leaning full-stack engineer who has built a multi-tenant AI-powered widget and admin dashboard platform used across 40+ merchant websites. Strong in TypeScript/Next.js/GraphQL systems design, reusable platform primitives, and cross-layer debugging, with a clear track record of shipping scalable product experiences under ambiguity.”
Christopher Sipola
Senior Machine Learning Engineer specializing in LLMs and recommendation systems
“ML/GenAI engineer who owned major parts of Spotify’s AI DJ from offline experimentation through deployment, monitoring, and iteration. They combine recommender systems, RAG, real-time feedback loops, and LLM safety/orchestration to ship consumer-facing personalization features that drove double-digit engagement and deeper listening sessions.”
Sudheer Bommichetty
Mid-level Machine Learning Engineer specializing in NLP, MLOps, and Generative AI
“Built and deployed a production LLM conversational AI system at OpenAI supporting chat, summarization, and semantic search at 1M+ requests/day, driving major latency (40%) and accuracy (25%) improvements through Pinecone optimization and tighter RAG with re-ranking. Also has Amazon experience improving recommendation systems by translating ML metrics into business terms to boost CTR and conversions, with strong MLOps/orchestration depth (Airflow, MLflow, SageMaker, Kubeflow).”