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Vetted Google Cloud Platform Professionals
Pre-screened and vetted.
Uchechukwu Okechukwu
Mid-Level Software Engineer specializing in backend, distributed systems, and AI/LLM platforms
“Built and shipped AI-powered workflow automation at Oracle, including an MCP-based agentic workflow with tool-calling and guardrails, plus Grafana monitoring and Confluence documentation. Also led a Django monolith-to-microservices migration at Chamsmobile using blue-green deployment and load balancer traffic splitting to avoid regressions while modernizing production systems.”
Shubham Jangle
Intern Robotics Engineer specializing in autonomous navigation and perception (ROS2)
“Recent UC Riverside master’s graduate focused on uncertainty-aware imitation learning for indoor robot navigation, building a full ROS 2 Humble stack (perception, learned policy, uncertainty estimation) with adaptive speed control. Demonstrated strong real-time robotics debugging and systems skills, achieving 92% autonomous navigation success across 100 trials and improving reliability through uncertainty calibration and SLAM/loop-closure optimization.”
Ramya Konda
Mid-level AI/ML Engineer specializing in healthcare ML and generative AI
“AI/LLM engineer at Humana who built and deployed a HIPAA-aware RAG system for clinical record retrieval, cutting search time dramatically and improving retrieval efficiency by 30%. Experienced with Spark-scale data preprocessing, QLoRA fine-tuning, LangChain orchestration, and MLflow+SageMaker integration, with a strong testing/evaluation discipline (A/B tests, human eval) to hit 95%+ accuracy and production latency targets.”
“AI/ML engineer with banking domain experience (M&T Bank) who built a production credit-risk prediction and reporting platform combining ML models (XGBoost/TensorFlow) with a RAG pipeline (LangChain + GPT-4) over compliance documents. Delivered measurable impact (≈20% better risk detection/precision, 50% less manual reporting) and productionized workflows on Vertex AI/Kubeflow with CI/CD and monitoring; also implemented embedding-based semantic search using FAISS/Pinecone.”
Bhavya Sri Gunnapaneni
Mid-level AI/ML Engineer specializing in fraud detection and NLP
“Built production AI/RAG-style systems for message Q&A and insurance claims workflows, combining data ingestion, indexing/retrieval, and LLM integration with fallback modes. Has hands-on orchestration experience (Airflow, Prefect, LangChain) and cites large operational gains (claims processing reduced to ~45 seconds; manual review -50%; false alerts -30%) through automated, monitored pipelines and close collaboration with non-technical stakeholders.”
Atharva Deshmukh
Mid-level AI/ML Engineer specializing in GenAI and cloud MLOps
“Applied LLMs to high-stakes domains (wildfire risk for emergency teams and loan approval via a fine-tuned IBM Granite model), with a strong focus on reliability—using RAG-based cross-validation to reduce hallucinations and continuous ingestion pipelines (MODIS satellite imagery via AWS Lambda) to keep data current. Experienced in production orchestration and MLOps-style workflows using Airflow, AWS Step Functions, and SageMaker Pipelines, and collaborates closely with analysts on KPI-driven evaluation.”
PremKumar Gandla
Mid-level AI/ML Engineer specializing in MLOps, NLP, and scalable model deployment
“Built and deployed a production autonomous AI data analyst agent (LangChain + GPT + Streamlit on AWS) that turns natural-language questions into validated SQL, visualizations, and insights, cutting manual analysis time by ~50%. Emphasizes reliability and MLOps: schema-aware validation/guardrails to prevent hallucinations, scalable large-data processing, and Azure DevOps CI/CD + MLflow for automated deployment and experiment tracking.”
Srichandan Kota
Senior Full-Stack AI Engineer specializing in Generative AI and FinTech
“Backend engineer who built and owned an AI-powered financial research product end-to-end, using a typed NestJS/GraphQL backend with LangGraph-style agent routing to produce sourced, structured financial analysis. Emphasizes finance-grade correctness (Zod validation, metric registries, unit/empty-result guardrails) while keeping latency low via batching, caching, and fast token streaming, and has led incremental migrations using strangler/feature-flag/shadow traffic patterns.”
Veena Vyshnavi Garre
Senior Full-Stack Software Engineer specializing in cloud-native systems and AI/ML
“Backend engineer who significantly evolved an internal Resource Manager platform, moving from a monolith to microservices and improving onboarding speed while reducing integration errors. Has hands-on experience building reliable and secure Python/FastAPI APIs (Pydantic schemas, circuit breakers, caching, metrics/alerts) and leading zero-downtime migrations with strong data integrity patterns (dual writes, idempotency, reconciliation checks).”
Uday Dorawala
Director-level Engineering Leader specializing in SaaS platforms, data, and cloud modernization
“Former founder with an acquired venture who later led R&D at McClatchy and joined multiple startups. Identified a major client need and built a mobile app platform using ML and AR for home builders, driving adoption by dozens of customers and $1M+ ARR. Strong hands-on builder who can architect MVPs, iterate quickly with A/B testing and user feedback, and scale early engineering teams and culture.”
Manvi Panjwani
Mid-level Machine Learning Engineer specializing in cloud, governance automation, and distributed systems
“Governance engineer intern at GSK who built policy-as-code automation using Open Policy Agent/Rego integrated into GitHub CI/CD and Terraform workflows. Also built and shipped a voice-enabled expense tracking app using speech-to-text + LLM structured extraction with strong validation, retries, and semantic guardrails, and designed the supporting PostgreSQL data model with performance-focused indexing.”
Ranxin Li
Mid-Level AI/Full-Stack Engineer specializing in agentic LLM systems and RAG
“Built and deployed Clyra.AI, an AI-driven daily scheduling product that uses a LangGraph-based multi-agent LLM pipeline (task extraction, verification, reflection) grounded with strict RAG over emails/documents/calendars and real-world signals like health metrics. Designed a custom agent orchestrator with bounded loops/termination conditions and a self-auditing verification/reflection layer to reduce hallucinations while controlling latency and cost via caching and model distillation.”
Haritha Kuraparthi
Mid-level Full-Stack Developer specializing in cloud data engineering and analytics
“Software developer with hands-on experience owning customer-facing work end-to-end (requirements, implementation, testing, and feedback-driven iteration) using Python and React.js. Also described remodeling an internal legacy page/tool to improve performance and accuracy, and has exposure to microservices and RabbitMQ plus ETL-based system work.”
Soham Ravindra Lokhande
Junior Software Engineer specializing in agentic automation and AI platforms
“Backend-leaning founding/early engineer who built automation platforms end-to-end: FastAPI/Python services integrated with a Next.js/TypeScript frontend, including a production VNC streaming URL endpoint for cloud-instance desktop viewing. Also designed core Postgres user/workflow data models and built an agentic orchestration system with LangChain/LangGraph (sub-agents, validators, pause/resume), plus made scalability tradeoffs like S3 pre-signed uploads to keep microservices responsive.”
Brian Carroll
Principal Cybersecurity & Network Infrastructure Leader specializing in cloud, zero trust, and SIEM
“Founder of a self-funded IT management consulting practice specializing in security, compliance, and risk engineering for highly regulated sectors (banking/finance, healthcare, energy, defense, telecom). Uses consulting engagements to build repeatable “military-grade” security foundations and identify recurring pain points, with a longer-term goal of transitioning from consulting into a sustained internal team role for deeper impact.”
Shawn Faber
Executive Engineering Leader specializing in enterprise SaaS, AI/ML, and cloud modernization
“Commercially minded candidate with exposure to private equity firms as sales targets and experience building partnerships around venture-backed company ecosystems. They appear more inclined to join an existing company than found one, bringing a metrics-driven, process-oriented approach and creative execution style with a strong focus on clear growth paths and capital stability.”
Hari Billa
Mid-level Data Scientist specializing in machine learning, NLP, and healthcare AI
“Senior data scientist with hands-on ownership of production ML and GenAI systems across enterprise churn, clinical Q&A, and real-time fraud detection. Stands out for combining strong MLOps discipline with measurable business impact, including $2M+ retained revenue, 10K TPS low-latency fraud infrastructure, and a clinician-reviewed RAG system that improved retrieval accuracy by ~38%.”
Ruturaj Dixit
Junior Data Scientist specializing in AI/ML and product analytics
“Applied ML/data scientist who has owned backend-heavy AI systems end-to-end, including a market-signal platform on FastAPI/AWS and rapid MVP delivery in medical computer vision. Particularly interesting for teams needing someone who can combine model development, backend APIs, production debugging, and pragmatic low-latency architecture decisions.”
Nidhip Patel
Mid-level Software Engineer specializing in AI/ML and full-stack systems
“Backend Java engineer with strong platform/DevOps experience: modernized an insurance claims legacy monolith into DDD-aligned microservices, deployed containerized services on Kubernetes with Jenkins CI/CD and static analysis gates, and implemented GitOps using ArgoCD. Also led major AWS migration planning with dependency mapping and network monitoring to uncover hidden dependencies, and built Kafka-based real-time event streaming with schema-registry-driven evolution.”
Ramya Sree Kanijam
Mid-level Software Engineer specializing in backend systems, cloud, and AI pipelines
“Built and owned an end-to-end AI-driven content enrichment pipeline for a news workflow, using n8n, LLM agents, and external APIs to automate ingestion, deduplication, categorization, and approval routing. Stands out for production-minded AI systems work: they improved reliability with schema validation, retries, idempotency, and monitoring, while automating 90% of processing and cutting duplication errors by 95%+.”
Dinesh Guguloth
Mid-level Software Engineer specializing in full-stack cloud-native and AI applications
“Full-stack engineer with cloud and GenAI experience who has owned production features end-to-end, including a reporting dashboard optimized from 14s to 5s using query/API refactoring and monitored via AWS CloudWatch. Also productionized an OpenAI-powered chatbot using LangChain with prompt design, guardrails, and evaluation via production logs and user feedback, and has led incremental legacy-to-microservices modernization with parallel run to avoid regressions.”
Jay Patil
Mid-level Full-Stack AI/ML Engineer specializing in LLMs and intelligent systems
“Built a semantic search portal for a fellowship department and an AI-driven PR review pipeline, using AI selectively for boilerplate while retaining full ownership of architecture, security review, testing, and deployment. Has hands-on experience with multi-agent systems, monitoring, and security validation, with a notably disciplined approach to catching false positives and rewriting weak AI output.”
Praneeth Gunasekaran
Senior Mobile Software Engineer specializing in secure React Native and Bitcoin wallets
“Built and evolved the backend-adjacent platform for a self-custody Bitcoin wallet used by 2000+ users, emphasizing security-first architecture that avoids custodial risk by keeping private key operations client-side. Demonstrates strong API reliability and security depth (FastAPI contract-first design, idempotency, state-machine modeling, JWT/device-aware auth) and has reduced production failures by hardening signing flows against poor connectivity.”