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Vetted Docker Professionals
Pre-screened and vetted.
Kim Go
Principal Enterprise Architect specializing in AI, cloud modernization, and cybersecurity
“Senior technologist (25 years experience) who served as chief architect/CTO for a patented software startup that was acquired. Strong at building scalable, robust, technology-agnostic systems and translating technical value into investor-ready narratives (forecasts, roadmaps, documentation). Currently prefers joining an existing founding team as a key technical leader/mentor rather than leading entrepreneurship solo.”
Poojith Madduru
Mid-level Software Engineer specializing in Healthcare IT & HL7 FHIR interoperability
“Backend/platform engineer with Optum experience owning a production FHIR Member Access API aligned to CMS interoperability requirements. Built and scaled Spring Boot/HAPI FHIR microservices on AWS (Docker/Kubernetes) with zero-downtime CI/CD, and operated them with strong observability (Dynatrace, logs/metrics, alerting) and incident response. Also implemented a Kafka-based FHIR bulk data pipeline with schema versioning, idempotent processing, and reliable backfills/replays.”
Sandesh Shridhar
Senior Full-Stack AI Engineer specializing in LLM and RAG applications
“Consulting-style LLM practitioner who builds enterprise knowledge assistants using RAG and takes them from prototype to production with guardrails, evaluation, and full-stack observability. Experienced partnering with IT and customer-facing teams to demo solutions, build tailored prototypes, and drive adoption through API-based integration.”
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.”
Shashi Kiran
Mid-level Full-Stack .NET Developer specializing in Azure, APIs, and Angular SPAs
“Frontend-focused engineer with enterprise Angular experience integrated with .NET APIs, emphasizing production-ready practices (reusable components, modular architecture, TypeScript standards, Jasmine unit tests, and CI/CD). Has not built Unreal Engine UI systems yet, but articulates how they would translate web UI modularity, separation of concerns, and testing/automation practices to Unreal/CommonUI workflows.”
Deepanjay Nandal
Software Engineering Intern specializing in real-time analytics and distributed systems
“Built a production AI legal search platform that uses a retrieval-first, source-grounded LLM pipeline with confidence-based fallbacks and structured, traceable outputs to reduce hallucinations and improve trust. Also has experience at Discover Excellence building real-time analytics and identity stitching systems, emphasizing conservative data validation, idempotent processing, and fault-tolerant queue-based workflows.”
Aakanksha Desai
Junior Full-Stack Software Engineer specializing in React, Kubernetes, and AI-powered apps
“Backend/DevOps-leaning engineer managing multiple customer service platforms end-to-end (requirements through deployment). Built an in-house Python monitoring/alerting solution for Salesforce-to-Java contact sync jobs (Snowflake dependencies) that increased uptime ~60%, and helped modernize delivery by moving the team from manual releases to automated Jenkins-based deployments while coordinating an Oracle EBS→Fusion transition with business/data/IT stakeholders.”
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.”
Yat Pan Fung
Mid-level Full-Stack Developer specializing in web, mobile, and crypto trading systems
“Frontend engineer with experience building an e-commerce marketplace platform (Japan-to–Hong Kong) and designing a modular, message-queue-driven architecture for scalability and reliability. Built a high-frequency, massive-state React+TypeScript interface using Redis event streaming and JSON Patch, reporting ~10x–20x performance gains over polling/immutable approaches.”
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.”
prashansa chaudhary
Mid-Level Full-Stack Software Engineer specializing in cloud-native data platforms and AI apps
“Software engineer who has owned customer-facing/internal platforms end-to-end, emphasizing fast iteration through small releases backed by monitoring and rollback safety. Built SurveyAI with reusable React/TypeScript components and a stateless Node.js REST backend with clear API contracts/validation, and created an internal Airflow + AWS Lambda automation tool integrated with Slack alerts to reduce manual work and improve response time.”
Manasa Pippera
Senior .NET Full-Stack Developer specializing in cloud, IoT messaging, and real-time web apps
“Full-stack engineer who owns customer-facing web products end-to-end (React/TypeScript + Node.js), shipping frequent releases with strong testing, staged deploys, and production monitoring. Improved a key user flow by batching backend calls and simplifying frontend rendering, driving ~30% faster load times and ~30% higher completion rates. Also built an ops monitoring dashboard using ELK + Prometheus/Grafana that cut incident response time by 40% and has hands-on microservices messaging experience (RabbitMQ/Kafka, idempotency, DLQs).”
Nidhip Patel
Mid-Level Software Development Engineer specializing in Java microservices and cloud deployments
“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.”
Susheel Thimlapur
Mid-Level Full-Stack Software Engineer specializing in React, Node.js, and AWS
“Software developer at Indiana University who built a phishing training platform using TypeScript/React, Node, GraphQL, and DynamoDB, including an admin tool to monitor student completion and send automated reminder emails. Also created TechRent, an IU-only electronics rental marketplace concept focused on improving security by restricting access to university students.”
Ron Lei
Junior QA Automation Engineer specializing in Playwright E2E and API testing
“QA automation-focused engineer who hardens production CI/CD by integrating and stabilizing end-to-end automated tests (tackling async UI flakiness, resilient assertions/selectors, and controlled test data). Demonstrates strong cross-layer troubleshooting by correlating logs and system metrics to resolve intermittent service reachability, then adding monitoring/alerts and documentation. Also partners directly with operators to improve real-world workflows by enhancing validation logic and error messaging.”
Swati Swati
Senior Data Scientist/Software Engineer specializing in ML systems and cloud DevOps
“AI software engineer with experience spanning LLM/RAG production systems and regulated fintech infrastructure. Built an end-to-end natural-language-to-SQL analytics assistant (Weaviate + GPT-4 + Supabase) shipped as an API with 92% accuracy and major time savings for non-technical users, and also owned demand-forecasting and CI/CD/containerization improvements for a Bank of America core banking deployment at Infosys.”
Prasad Krishna
Mid-level Full-Stack Developer specializing in healthcare analytics and microservices
“Built and maintained an air-quality prediction backend in Python/Flask that serves offline-trained ML models to a React dashboard via JSON REST APIs. Demonstrates strong performance focus across the stack—low-latency inference under load, SQLAlchemy/Postgres query optimization, multi-tenant data isolation, and caching/background task strategies for high-throughput systems.”
Srilalitha Subbaswamy
Junior Software Engineer specializing in cloud-native microservices and distributed systems
“Backend/ML platform engineer who built an end-to-end news summarization and personalized recommendation system using FastAPI, Redis, and a vector search pipeline (FAISS). Strong in productionizing services on Kubernetes with GitOps (ArgoCD + GitHub Actions), including CI image tagging/publishing and safe rollouts, plus experience migrating EC2 services to containerized orchestration with robust health checks and latency/error monitoring.”
Visaj Kapadia
Mid-Level Full-Stack Developer specializing in AWS and scalable web platforms
“Software engineer with hands-on AWS experience optimizing an email campaign delivery system—re-architected a monolithic worker into multi-threaded/multi-worker ECS components to boost throughput ~600% (5 to 35 emails/sec). Comfortable debugging production issues (e.g., SQS/EventBridge policy misconfiguration) and emphasizes maintainable delivery via design docs, TDD, versioned APIs, and strong test coverage.”
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.”
Gabriel Fagundes
Mid-level AI/ML & Backend Engineer specializing in AI platforms and computer vision
“Backend engineer with hands-on experience building real-time, low-latency systems: owned the Python backend for a real-time crowd-monitoring product (top 5% at HackHarvard 2025) using OpenCV, GPU YOLO inference (PyTorch), WebRTC, and OAuth. Also has production Kubernetes/GitOps experience (Helm/Kustomize, GitHub Actions, Argo CD), Kafka-based event pipelines, and executed a minimal-downtime on-prem PostgreSQL migration to AWS EC2.”