Vetted Google Cloud Platform Professionals

“Backend engineer with healthcare-domain experience building a security-critical RBAC identity/authentication/authorization microservice suite used across hospital imaging platforms (X-Ray, Ultrasound, etc.). Demonstrates strong security mindset (mTLS, cert hygiene, JWT, pen-testing collaboration) and pragmatic scaling/reliability practices (Nginx load balancing, Redis caching, automated tests, canary rollouts).”

“Co-founded a Digital Loss Prevention (DLP) startup and raised $6M in seed funding by showcasing a controlled, laptop-based technology demo. Post-funding, drove MVP planning and execution by sequencing operations and assembling a team to build an appliance MVP, using an iterative build/evaluate/visualize approach.”

“Built and shipped a production-grade GenAI Fraud & Compliance Investigation Copilot for a large US bank, integrating OCR docs, structured data, and prior case history to generate grounded, regulator-friendly summaries and red-flag highlights. Demonstrates strong end-to-end LLM systems engineering (LangGraph/LangChain, hybrid retrieval with FAISS+BM25, guardrails/citations, streaming/latency optimization) plus rigorous evaluation and close partnership with compliance stakeholders.”

“React-focused engineer who built a full-stack analytics/test-metrics dashboard (React frontend + Python backend) and turned common UI pieces (data tables, filter panels, chart wrappers) into a reusable internal component library with docs, examples, and basic tests. Strong on profiling-driven performance optimization (React Profiler, memoization) and on owning ambiguous internal-tool projects end-to-end; now planning to package internal patterns into public open-source components.”

“Robotics software/perception engineer with production AMR experience at Symbotic, building a real-time SKU case re-identification pipeline used in high-volume Walmart/Target warehouse operations. Strong in ROS2 + Docker deployments on Jetson (TensorRT quantization) and system-level performance debugging, including cutting inference latency from ~13s to ~2s through architecture changes. Also has lab experience integrating SLAM/MPPI/behavior trees for rule-compliant navigation and distributed perception-to-UR5e manipulation systems (MoveIt/ros_control) with multi-camera sensing and 3D reconstruction.”

“Software engineer with experience at Google and the City and County of San Francisco building production AI systems, including a RAG-based internal support chatbot and ML-driven ticket priority tagging. Has scaled data/ML platforms with Airflow on GCP (1M+ records/day, 99.9% SLA) and deployed multi-component systems with Docker and Kubernetes (GKE), using modern LLM tooling (LangChain/CrewAI, Claude/OpenAI, Pinecone/ChromaDB, Bedrock/Ollama).”