Vetted Google Cloud Platform Professionals

“Accenture data/ML practitioner who deployed a retail churn prediction and BERT-based sentiment analysis system to production, integrating behavioral + feedback data and operationalizing it with ETL automation, orchestration, and CI/CD. Experienced managing 2TB+ multi-source data, monitoring drift in Databricks, and translating results into Power BI dashboards for marketing teams (including K-means customer segmentation).”

“Backend engineer who has delivered large, measurable performance wins (10x throughput, 67% latency reduction) by combining Flask microservices, Redis caching, and AWS autoscaling/observability. Has hands-on depth in SQLAlchemy/Postgres optimization and production scaling pitfalls (cache consistency, connection exhaustion), plus experience deploying real-time ML inference (XGBoost) on AWS Lambda and building secure multi-tenant Kubernetes isolation.”

“Full-stack Java developer with IBM and Epic Systems experience modernizing legacy enterprise apps into microservices and delivering customer-facing healthcare claims workflows at very high scale (2M+ transactions/day). Strong blend of product engineering (APIs + React/TypeScript UI) and production operations on AWS, including performance incident remediation via query optimization, indexing, and autoscaling.”

“QA Automation Engineer with 7+ years building dependable enterprise automation suites across UI, API, and database layers using Selenium (Java), Playwright, Karate, and Cypress. Integrates smoke/regression suites into CI/CD (GitLab/Jenkins/GitHub Actions) with reporting and notifications, and has prevented production issues by catching silent backend failures and high-impact payment defects through end-to-end validation and strong root-cause evidence.”

“ML/LLM engineer who has shipped production RAG systems (LangChain + HF Transformers + FAISS) with hybrid retrieval and cross-encoder re-ranking, deployed via FastAPI/Docker/Kubernetes and monitored with MLflow. Also partnered with wealth advisors at Edward Jones to deliver a client retention model with SHAP-driven explanations and a dashboard that improved trust, adoption, and reduced high-value client churn.”

“Built and deployed a production compliance automation RAG system (at Citi) that generates citation-backed, schema-validated risk summaries for regulatory document review. Emphasizes regulated-environment reliability with retrieval-only grounding, abstention, confidence thresholds, and immutable audit logging, plus orchestration using LangChain/LangGraph and Airflow. Reported ~60% reduction in compliance review effort while maintaining high precision and traceability.”

“Senior technology/executive leader with 30+ years building and scaling mission-critical platforms across blockchain, cloud, cybersecurity, and fintech, including leading 100+ person global teams and managing $100M P&Ls. Founded Pharus (2022) after driving Web2-to-Web3/DeFi/metaverse initiatives at SDK Co, using a first-principles, PoC-driven approach to deliver secure, compliance-aware transformations (GDPR/NYDFS) and multi-million-dollar optimizations, with a focus on quantum-resistant Web3 and ethical AI governance.”

“Full-stack engineer who built and owned a generative-AI pipeline end-to-end inside the Vibecut video editor using Next.js App Router/TypeScript, Gemini-based prompt routing, and Zustand state management, including concurrency-safe requests. Also integrated Python services to access newly released AI tooling, optimized Postgres/S3 data flows for thumbnails, and built Modal-to-Amplitude workflows for Reddit-driven sentiment/metrics in a pre-seed environment while also handling marketing.”

“AI engineer with hands-on production experience building an end-to-end RAG system that reduced document-answering time from hours to minutes, improving accuracy through chunk overlap and hybrid BM25+semantic retrieval. Also built a LangGraph-based agent that researches company financial news via web search (Google Serper), using Pydantic structured outputs and checkpointing for reliability; experienced collaborating with non-technical stakeholders at JPMC and communicating ROI.”

“Backend-focused engineer with production experience building Spring Boot services for automated workflow and data-processing platforms, using queues plus retry and idempotency patterns. Also uses Python to automate data processing; emphasizes testing and peer review for maintainability.”

“Software engineer with hands-on ownership of both fintech checkout improvements (saved payment methods/one-click checkout with tokenization and feature-flag rollouts) and production LLM/RAG systems for customer support. Demonstrates strong operational rigor via guardrails, evaluation loops integrated into CI/CD, and scalable data pipelines handling messy PDFs/CSVs/logs with reliability and observability.”

“Built a production internal LLM-powered knowledge assistant using a RAG architecture (Python, LLM APIs, cloud services) that answers employee questions with sourced, grounded responses from internal documents. Demonstrates strong practical depth in retrieval tuning (chunking/metadata filters), orchestration with LangChain, and production reliability practices (latency optimization, automated embedding refresh, evaluation metrics, logging/monitoring) while partnering closely with non-technical operations teams.”

“Built and shipped a production browser automation LLM agent with a structured 4-stage workflow (plan/browse/extract/verify), emphasizing reliability via schema validation (Pydantic), constrained tool use, and contextual retry loops. Reports ~60% accuracy on the WebArena benchmark and monitors runs via console output and the Agno framework GUI, prioritizing accuracy over speed.”

“Data engineer with healthcare and enterprise experience (Molina Healthcare, Dell Technologies) building and operating high-volume batch + streaming pipelines across AWS and Azure. Strong focus on data quality (schema validation, fail-fast checks), reliability (monitoring/alerts, retries), and performance tuning (Spark/partitioning), with measurable runtime reduction and improved downstream trust.”

Jaideep bommidi

Screened

Senior ML Engineer & Data Scientist specializing in LLM agents, retrieval/ranking, and MLOps

Denton, TX8y exp

“Machine Learning Engineer currently at Webster Bank building an enterprise-scale LLM agent for Temenos Journey Manager/Maestro, using RAG-style multi-stage retrieval with FAISS/Pinecone, hybrid dense+sparse search, and LoRA fine-tuning optimized via NDCG/MAP and A/B testing. Previously handled messy incident/telemetry data at Deuta Werke GmbH with deterministic + fuzzy entity resolution, and has strong production data engineering experience across Spark/Hadoop and Python ETL systems.”

Prachika Agarwal

Screened

Senior Solutions Architect and Data Analyst specializing in cloud data platforms and experimentation

New York, NY4y exp

“Software engineer who built and scaled an internal automation/auditing tool for analyzing Google and Adobe tagging containers, adopted by 13 internal clients and saving ~15 hours per audit. Has experience shipping containerized, Kubernetes-orchestrated systems and integrating OpenAI APIs into an agentic chatbot feature (plus prior NLP chatbot work during a Cyber Peace Foundation internship).”

Bryan West

Screened

Senior Software Engineer specializing in AI, cloud infrastructure, and full-stack development

Chantilly, VA17y exp

“ML/NLP engineer who built a production system that converts large-scale unstructured text into a connected, searchable knowledge base using spaCy + Sentence Transformers/FAISS and a Neo4j knowledge graph, with BERTopic and XGBoost for organization/labeling. Strong focus on production-grade Python workflows (FastAPI/Celery, Pydantic validation, Docker, AWS ECS/Lambda) and robust entity resolution with measurable precision/recall and human review for low-confidence matches.”

Sai Vamsi

Screened

Mid-Level Software Engineer specializing in backend microservices and cloud-native systems

TX, USA4y exp

“ServiceNow engineer who built an AI-powered ticket summarizer end-to-end (RAG with vector DB + GPT, Redis latency optimizations, fallback summarization, and a React UI widget for agent feedback). Also has hands-on ROS 2 experience building real-time sensor-fusion nodes (LiDAR/IMU), debugging SLAM/navigation issues via rosbag + EKF tuning, and bridging heterogeneous robots by translating ROS 2 topics to MQTT/JSON. Strong DevOps background with Docker, Jenkins CI/CD, and Kubernetes orchestration for scalable deployments.”

Dan Sorensen

Screened

Executive CISO specializing in cybersecurity strategy, AI governance, and enterprise risk

Denver, CO10y exp

“Founder of Nexus Security Advisors, an early-stage cybersecurity consulting firm focused on supporting small and mid-sized businesses with practical security needs. Brings cybersecurity leadership plus AI governance and compliance focus, and has experience designing and delivering hands-on cyber threat intelligence training by validating needs with leadership and partnering to build a practical curriculum.”

Sai Chatrathi

Screened

Mid-level AI/ML Engineer specializing in healthcare analytics and MLOps

NY, USA4y exp

“Built and deployed a production LLM-powered lesson adaptation platform for K–12 educators that personalizes content for multilingual and neurodiverse students using RAG and content transformation. Owned the full stack from FastAPI backend and OpenAI integration through reliability/safety controls, latency/cost optimization, and weekly shippable modular APIs, iterating directly with curriculum stakeholders to reduce hallucinations and improve educator trust.”

Hetvi Shah

Screened

Mid-Level Full-Stack Software Developer specializing in React/Angular and Node.js

Toronto, Ontario6y exp

“Frontend lead who owned architecture and quality for TELUS’s Next Generation Sales Platform, building a modular React+TypeScript experience that scaled across wireline/wireless products and channels. Experienced in hardening UIs against unreliable backend integrations (API abstraction, retries/fallbacks, caching, logging) and delivering real-time dashboards via WebSockets, with strong CI/CD testing and blue-green release practices for high-stakes launches like Black Friday.”

Mike Khorrami

Screened

Director-level Engineering Leader specializing in enterprise SaaS and cloud-native platforms

Woodland Hills, CA25y exp

“Engineering leader/player-coach who modernized a legacy C#/SQL Server system to Snowflake + Python on GCP, enabling ~30x scale and supporting hundreds of millions of transactions per day per customer. Strong in architecture tradeoffs (Snowflake vs Databricks), production reliability (New Relic, logging/alerting), and lightweight process improvements like a rigorous Definition of Done and structured PR reviews.”

Divyansh Agarwal

Screened

Junior Machine Learning Engineer specializing in computer vision and LLM applications

New York, NY3y exp

“Built and led an autonomous driving software effort for Formula Student, owning the full autonomy stack (perception, planning, control) orchestrated in ROS. Implemented stereo depth + YOLO object detection, RRT/RRT* planning, and a robust SLAM pipeline (Kalman filter, submapping) while leveraging Gazebo simulation and modern deployment tooling (Docker/Kubernetes, AWS, GitHub Actions CI/CD).”

Ti Wu

Screened

Junior Full-Stack Developer specializing in web apps and reinforcement learning

Hsinchu, Taiwan1y exp

“Built an AI basketball shooting coach that analyzes player form against NBA players and recruited 30+ beta users via Reddit to drive iterative UI/workflow improvements. Also has internship experience building an administrative server and coordinating API/database compatibility with another client server, emphasizing communication and integration quality.”