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Vetted Google Cloud Platform Professionals
Pre-screened and vetted.
Principal DevOps/SRE Engineer specializing in multi-cloud infrastructure and DevSecOps
Intern Software Engineer specializing in distributed systems and FinTech
Mid-level Data Scientist specializing in marketing analytics and scalable data platforms
Senior Data Scientist specializing in Generative AI, NLP, and MLOps
Senior Full-Stack Software Engineer specializing in cloud-native microservices and FinTech
Senior DevOps / Cloud / Site Reliability Engineer specializing in AWS and Kubernetes
Senior Applications Engineer specializing in ERP Financial Systems and GenAI automation
Junior Full-Stack Software Engineer specializing in SaaS and AI-powered web apps
Executive CTO/CPO and Product & Technology Leader specializing in Healthcare SaaS and AI/ML
Mid-level Data Engineer specializing in cloud data platforms and streaming pipelines
Mid-level Data Engineer specializing in AI/ML data platforms and real-time streaming
Mid-level Data Engineer specializing in streaming and cloud lakehouse platforms
Director of Engineering specializing in AI/ML, data platforms, and consumer messaging
Senior Scrum Master and Agile Project Leader specializing in enterprise transformation
Mid-level Full-Stack Engineer specializing in web, mobile, and startup product development
Mid-level Software Engineer specializing in AI systems and FinTech
Junior Software Engineer specializing in backend, cloud, and AI-enabled enterprise systems
Executive Engineering Leader specializing in Telehealth Platforms and Healthcare IT
Senior Software Engineer specializing in distributed systems, IoT, payments, and blockchain
Senior AI/ML Engineer specializing in Generative AI and cloud-native ML systems
Rubeena Riyas
Senior AI Engineer specializing in LLM agents, RAG, and scalable data platforms
“ML/data engineer who owned an end-to-end production sales analytics pipeline at 15,000+ user scale, delivering ~50% compute reduction, ~80% faster reporting, and ~$1.2M impact. Also shipped a production RAG-based AI assistant over internal BigQuery/docs with evaluation metrics and safety guardrails, and built shared Python libraries to standardize reliability and accelerate engineering teams.”
Abhishikth Meesala
Mid-level AI/ML Engineer specializing in NLP, Generative AI, and fraud detection
“At PwC, built and productionized an agentic RAG enterprise search assistant over 6M internal documents (8M embeddings), deployed across AWS and GCP. Drove major retrieval gains (72%→92% precision via BM25+dense hybrid with RRF and cross-encoder re-ranking), reduced hallucinations 30%, achieved <2s latency at 50–60K queries/month, and cut support tickets 30%—boosting adoption to 2,500 users by adding source-cited answers.”