Vetted Google Cloud Platform Professionals

“LLM-focused customer-facing engineer who repeatedly takes document Q&A and agentic prototypes into secure, monitored production systems. Experienced in reducing hallucinations via RAG + guardrails, diagnosing retrieval/embedding issues in real time, and partnering with sales to run metrics-driven PoCs that overcome accuracy/security objections and drive adoption.”

“Built a production LLM/RAG-based “model excellence scoring” system at Uber to automatically evaluate hundreds of ML models, standardizing quality assessment and cutting evaluation time from days to minutes on GCP. Also delivered an NLP document classification solution for insurance claims at Globe Life, partnering closely with compliance/operations and improving routing accuracy from ~85% manual to 93% with the model.”

“Data engineer with eBay experience owning end-to-end pipelines for real-time order and user behavior analytics at 10M+ records/day. Strong in PySpark/SQL transformations, Airflow reliability patterns, and production observability (CloudWatch), with measurable outcomes including improved data quality and 30–40% query performance gains. Also built Python data APIs for analytics/ML consumers with versioning and backward compatibility.”

Travoy Spelling

Screened

Senior Data Scientist / ML Engineer specializing in GenAI, LLMs, and NLP

Texarkana, TX10y exp

“ML/NLP engineer focused on production GenAI and data linking systems: built a large-scale RAG pipeline over millions of support docs using LangChain/Pinecone and added a LangGraph-based validation layer to cut hallucinations ~40%. Also built scalable PySpark entity resolution (95%+ accuracy) and fine-tuned Sentence-BERT embeddings with contrastive learning for ~30% relevance lift, with strong CI/CD and observability practices (OpenTelemetry, Prometheus/Grafana).”

Alexander Goldberg

Screened

Executive Technology & Product Leader specializing in AI/AR SaaS and cybersecurity

Los Angeles, CA30y exp

“Engineering/technology leader with mission-critical experience at JPL NASA on the Mars Curiosity Rover, delivering an AI-driven navigation system designed for zero tolerance for mistakes and reportedly operating with no failures for 15+ years. Also led a monolith-to-microservices, cloud-native migration that improved scalability by 300% and cut deployments from days to hours, and is comfortable switching between executive fundraising/stakeholder communication and deep technical leadership.”

Byron Pineda

Screened

Staff/Lead Data Scientist specializing in Generative AI, NLP/LLMs, and MLOps

Pascagoula, MS10y exp

“Lead Data Scientist (10+ years) with recent work in healthcare data: built production pipelines that unify EHR, genomics, and clinical notes using NLP (spaCy/BERT/BioBERT) and scalable Spark-based processing. Also led development of domain-specific LLM/NLP systems for chatbots and semantic search, deploying models via FastAPI/Flask and improving retrieval with FAISS-backed, fine-tuned clinical embeddings and RAG-style workflows.”

Anand Madhusoodanan

Screened

Executive HR Tech & Salesforce Architect specializing in AI-driven recruiting automation

Bengaluru, India9y exp

“Co-founder of an HR tech startup who took an LLM-centered skill intelligence engine from prototype to production to deliver explainable, skill-based resume insights as an alternative to black-box ATS screening. Previously worked in consulting (Deloitte, Stand Up, Brilio), with experience in technical demos/workshops, pre-sales scoping, and supporting large deal cycles (including a ~$1M UK automotive client).”

Cornelius O'Donnell

Screened

Director-level Engineering & Program Leader specializing in AI product platforms

San Diego, CA25y exp

“Technical Program Manager and one of three internal "founders" of HP’s Hardware-as-a-Service home printer subscription initiative, spanning DTC shipping, simplified setup, ink replenishment, and warranty coverage. Led roadmap definition/execution, scaled delivery rapidly to 15+ scrum teams (including vendors) with SAFe-like coordination and shared engineering standards, and drove key architecture trade-offs (building an interim subscription management service) to accelerate time-to-market by about a year.”

Sarath Dunga

Screened

Mid-level Full-Stack Developer specializing in cloud microservices and AI/ML integration

Remote, USA4y exp

“Full-stack engineer (~3 years) with eBay production experience building and operating high-scale, event-driven Python microservices for order processing and AI-powered recommendations (Kafka/Redis/FastAPI on AWS with Prometheus/Grafana). Also delivered polished React+TypeScript analytics dashboards and designed high-concurrency PostgreSQL schemas with significant latency reductions. Recently built AI-agent orchestration and an interactive node-based requirements dashboard for Siemens Polarion via MCP servers, improving user interaction by ~17.8%+.”

ChinmaySanjay Kawle

Screened

Junior Software Engineer specializing in cloud developer tools and backend APIs

Seattle, WA2y exp

“Summer intern on AWS Lambda tooling team who shipped Finch support in AWS SAM CLI, adding OS/runtime detection and robust fallback behavior to preserve Docker compatibility across developer environments. Also built an end-to-end RAG system for querying arXiv quantitative finance papers using Postgres/pgvector with two-stage retrieval, citation-grounded prompting, and rigorous evaluation loops driven by IR metrics and user feedback.”

Saiteja Gaddam

Screened

Mid-Level Data Engineer specializing in cloud data platforms and streaming analytics

3y exp

“Data engineer (Intuit) who owned an end-to-end telemetry and subscription analytics platform processing ~22M events/day, built on Kinesis/S3/Glue/Spark/Airflow/Redshift. Strong focus on reliability and data quality (schema drift controls, quarantine layers, idempotent reruns) and performance tuning, achieving a reporting latency reduction from ~15 minutes to under 4 minutes while enabling revenue and churn analytics for business teams.”

Ranganayak Meravath

Screened

Mid-level Generative AI Engineer specializing in RAG, agentic copilots, and regulated AI

5y exp

“Senior engineer who built and productionized an Azure-based Enterprise AI Copilot for financial/compliance teams, focused on grounded, auditable answers with citations to reduce hallucinations in regulated workflows. Experienced designing multi-step agent orchestration and improving reliability through targeted iterations (e.g., fixing chunking/parsing to materially improve citation accuracy), plus building defensive pipelines for messy ERP/operational finance data.”

Cheryl Qian

Screened

Junior Product Designer specializing in AI-powered SaaS products

New York, NY3y exp

“Product-minded designer/builder who operates at the intersection of UX, support, and engineering. At Miter, they helped launch three products and built the customer-facing readiness layer that contributed to a 15% adoption increase; at Yacht Labs, they designed and implemented high-polish React/Next.js experiences and proposed a spec-driven app generation system to make AI output more controllable and trustworthy.”

Sudhir Sagi

Screened

Executive technology and operations leader specializing in connected vehicle SaaS and IoT

Novi, MI28y exp

“Candidate indicated they do not have a business plan or startup, are not familiar with the venture capital/accelerator landscape, and explicitly requested to withdraw their application because the position does not seem like the right fit.”

“Built an AI-powered job outreach application for his own job search and took it from idea to production use, owning architecture, FastAPI backend, retrieval/generation pipeline, frontend workflow, deployment, and iteration. Especially compelling for teams needing a pragmatic full-stack engineer who can turn LLM-based product ideas into usable, maintainable tools with measurable workflow impact.”

Chitra Uppalapati

Screened

Entry-level Software Engineer specializing in full-stack and machine learning applications

Sunnyvale, CA1y exp

“Built production Python data integrations and dashboard automation for incident analytics, with a strong focus on data quality, observability, and reliability for leadership-facing reporting. Also translated an ambiguous manual creator evaluation process at startup Spring into an automated predictive scoring feature, showing a blend of backend data engineering, test automation, and cross-functional product thinking.”

“Built end-to-end LLM/RAG systems for biological data and scientific literature analysis in a drug discovery setting, helping researchers explore disease insights and treatment hypotheses faster. Combines applied GenAI product work with strong production engineering, including monitoring, retrieval optimization, reusable Python services, and scalable deployment on AWS/Kubeflow.”

“Engineer with hands-on experience using AI coding tools like Claude Code and Augment in daily development, combined with real-world distributed systems work at Arista Networks. Built or worked on a Go-based platform that separated RBAC, audit logging, and provisioning into asynchronously communicating services, enabling scalable and independently evolving access-control workflows.”

“Robotics software engineer at Tesla who led end-to-end development of a distributed real-time control and orchestration platform for autonomous systems. Deep production ROS 2 experience (nav2, slam_toolbox), with demonstrated wins reducing end-to-end latency 25–30%+ via profiling, multithreaded executors, and QoS tuning, plus simulation and deployment at scale using Gazebo/Webots, Docker/Kubernetes, and CI/CD.”

“LLM engineer who has deployed privacy-preserving, real-time workplace risk monitoring over massive enterprise chat/email streams, tackling latency, hallucinations, and extreme class imbalance with model benchmarking, RAG + fine-tuning, and a pre-filter alerting layer. Also built an agentic legal contract drafting system (Jurisagent) using LangGraph/LangChain with deterministic multi-agent control flow, structured outputs, and reliability-focused evaluation/telemetry.”

“Built and deployed a production healthcare medical review agent that automates call-transcript summarization and medication reconciliation using a hybrid deterministic + LangGraph-orchestrated LLM workflow. Demonstrates strong reliability engineering (guardrails, schema validation, confidence thresholds, golden/adversarial eval, Langfuse monitoring) in a regulated environment, delivering 60% lower latency and 70%+ efficiency gains while partnering closely with care managers and operations.”

“Software engineer with experience at PayPal and JPMC building large-scale onboarding/account setup systems using React/TypeScript with Spring Boot/Node microservices and Kafka. Also built an Ignition-based SCADA monitoring tool at Mainspring Energy that became the default for manufacturing/test engineers by aggregating real-time telemetry and historical test data.”

“Full-stack engineer (~4 years) who has owned and shipped customer-facing SaaS onboarding and a role-based real-time analytics dashboard using TypeScript/React with a modular backend. Experienced in microservices with RabbitMQ and strong observability practices (correlation IDs, structured logging, queue metrics), and built an internal deployment tracker integrated with CI/CD that replaced manual spreadsheet/Slack processes.”