Vetted Docker Professionals

Pre-screened and vetted.

PK

PRAJU KUMAR

Screened

Mid-level Full-Stack Developer specializing in Java/Spring microservices and React/Angular

USA6y exp
Brainvire InfotechAuburn University

Full-stack engineer with hands-on production experience building real-time customer-facing features (order tracking + push notifications) across React/React Native and Node/Spring Boot with Postgres/MySQL. Demonstrates strong reliability patterns (transactional outbox, background workers, idempotent webhook ingestion) and has deployed/operated systems on AWS (ECS/Fargate/ALB, CloudWatch, CodePipeline) with structured observability and environment separation.

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AA

Junior Software Engineer specializing in AI assistants and cloud-native backend systems

New York, NY2y exp
Novum AINYU

Founding engineer at Novum AI building a real-time call analytics/suggestion backend (transcription + sentiment/tone + context retrieval) using a serverless architecture. Drove major latency improvements (about 4s down to sub-1.5s) and has practical experience hardening production APIs (FastAPI/Pydantic, auth with Cognito/Redis) and payment systems (Stripe) by surfacing overlooked subscription and multi-tenant billing edge cases.

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HA

HARI ANDE

Screened

Junior Software Engineer specializing in backend microservices and GenAI automation

Alabama, USA4y exp
EquifaxKennesaw State University

Built and productionized an LLM/RAG-based credit case triage system that indexes credit bureau narratives and delivers structured, source-linked summaries for analysts. Emphasizes production reliability (data masking, human-in-the-loop review, abstention/fallbacks, monitoring) and reports >99% uptime plus ~30% efficiency gains, with iterative improvements driven by offline/online evaluation and schema-aware validation.

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MG

Mid-level Java Full-Stack Developer specializing in cloud-native microservices and React

Chesterfield, MO5y exp
Reinsurance Group of AmericaUniversity of Missouri-Kansas City

Full-stack engineer with hands-on ownership of real-time, Kafka-driven systems in production, spanning React/TypeScript frontends, Spring Boot/Node backends, and AWS (EKS/ECS/EC2) operations. Notable for modernizing legacy batch workflows into event-driven architectures with measurable impact (35% faster risk calculations, 30% better accuracy) and scaling to 2x volume using reliability patterns like idempotency, retries, and staged rollouts.

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MJ

Senior Unity/Simulation Developer specializing in VR training and interactive 3D applications

Austin, TX8y exp
Booz Allen HamiltonFull Sail University

Unity/C# developer with defense/USAF VR experience who built a first-of-its-kind real-time metrics/telemetry API layer (serialized + encrypted JSON over REST) that enabled in-engine performance assessment and drove third-party LMS dashboard requirements. Currently prototyping an AI-driven "DM" agent experience using OpenClaw with model switching (Ollama) and Claude Code for in-engine benchmarking while weighing self-hosted vs cloud LLM tradeoffs (security/latency/cost). Based in Austin, TX; prefers remote but open to relocation with assistance.

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Ramcharan SreenivasaReddy - Mid-level Full-Stack Developer specializing in FinTech platforms and cloud-native microservices in Texas, USA

Mid-level Full-Stack Developer specializing in FinTech platforms and cloud-native microservices

Texas, USA6y exp
Morgan StanleyUniversity of Central Missouri

Backend/platform-focused Python engineer who has owned FastAPI services with Postgres/SQLAlchemy and production-grade auth (JWT + RBAC). Experienced deploying and operating microservices on Kubernetes with GitOps (ArgoCD), HPA tuning, and Prometheus/Grafana monitoring, plus hands-on cloud-to-on-prem migrations and Kafka-based real-time streaming pipelines.

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Rupak Chand - Junior ML Data Associate specializing in AI training data and LLM prompt evaluation in Connecticut

Rupak Chand

Screened

Junior ML Data Associate specializing in AI training data and LLM prompt evaluation

Connecticut2y exp
AmazonSacred Heart University

Applied ML/embodied AI practitioner who built an on-device gesture-control system for smart-home lights using Raspberry Pi + camera, focusing on privacy-preserving real-time inference and hardware-constrained optimization (async pipeline + TF Lite INT8). Also made a high-impact architecture decision for an ML content evaluation/QA pipeline processing millions of annotated text samples weekly, reducing batch runtime from ~6 hours to ~40 minutes while lowering compute cost.

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Fatemeh Taghvaei - Junior AI/ML Engineer and Instructor specializing in deep learning, computer vision, and NLP in Chicago, IL

Junior AI/ML Engineer and Instructor specializing in deep learning, computer vision, and NLP

Chicago, IL2y exp
National Louis UniversityUniversity of Illinois Chicago

Computer-vision practitioner and educator who built a real-time license plate recognition system (OpenCV/Python + KNN) optimized to run on a Raspberry Pi with camera integration. Also designs hands-on deep learning coursework, incorporating recent transformer-based vision research (Vision Transformers) into practical labs on real datasets.

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Arunkumar Gangula - Senior Full-Stack Software Engineer specializing in distributed systems and cloud microservices in Tempe, Arizona

Senior Full-Stack Software Engineer specializing in distributed systems and cloud microservices

Tempe, Arizona11y exp
Arizona State UniversityArizona State University

Product-minded full-stack engineer from CouponDunia who owned end-to-end notification and recommendation services at million-user scale. Built internal admin/analytics and operations dashboards in React/TypeScript with typed contracts and scalable Node.js REST APIs, and has deep microservices experience with Kafka/RabbitMQ (idempotency, retries/DLQs, partitioning, consumer tuning, and observability).

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Nandini Reinthala - Mid-Level Full-Stack Python Developer specializing in AI and data platforms in Dallas, TX

Mid-Level Full-Stack Python Developer specializing in AI and data platforms

Dallas, TX5y exp
Fannie MaeUniversity of Central Missouri

Full-stack engineer who builds TypeScript/React SPAs on Python (Flask/FastAPI) backends and has hands-on experience integrating AI components (Azure OpenAI, LangChain, vector databases) into user workflows. Has built internal AI-enabled dashboards/search tools for analysts and business users, emphasizing typed API contracts, CI/CD-driven quality, and microservices reliability patterns (monitoring, retries, idempotency) at scale.

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Lokesh Jain - Senior Data Engineer specializing in cloud data platforms and ML pipelines

Lokesh Jain

Screened

Senior Data Engineer specializing in cloud data platforms and ML pipelines

5y exp
WayfairUniversity at Buffalo

Built and deployed AcademiQ Ai, a production LLM-based teaching assistant using GPT/BERT with RAG (LangChain + Pinecone) to handle large student notes and generate adaptive explanations/quizzes. Demonstrated measurable retrieval-quality gains (18% precision improvement, 22% less irrelevant context) by tuning similarity thresholds and chunking based on user satisfaction signals. Also orchestrated terabyte-scale, real-time demand forecasting pipelines using Airflow and Kubeflow on GCP with strong monitoring, shadow deployment, and feedback-loop practices.

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Manikanta Kopparapu - Mid-Level Full-Stack Software Engineer specializing in cloud-native web applications in TX, USA

Mid-Level Full-Stack Software Engineer specializing in cloud-native web applications

TX, USA4y exp
Community Dreams FoundationUniversity of North Texas

Full-stack engineer who has owned customer-facing and internal web portals end-to-end (API, database, React UI, and deployment). Experienced designing multi-service architectures with Node/Express and Java/Spring Boot plus RabbitMQ/Kafka messaging, emphasizing contract/versioning discipline, observability, and operational tooling that measurably reduces support load and manual work.

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Bhanu Gummadi - Mid-level Backend Software Engineer specializing in cloud-native microservices and FinTech in Bellevue, WA

Bhanu Gummadi

Screened

Mid-level Backend Software Engineer specializing in cloud-native microservices and FinTech

Bellevue, WA4y exp
MastercardUniversity of Central Missouri

Backend-focused engineer with Mastercard experience building and operating high-volume transaction-processing microservices. Has owned customer-facing banking services end-to-end and built an internal on-call analytics tool that centralized logs/metrics with real-time filtering to speed root-cause analysis and reduce incident investigation time.

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Nisarg Shah - Junior Machine Learning Engineer specializing in geospatial analytics and computer vision in Tempe, Arizona

Nisarg Shah

Screened

Junior Machine Learning Engineer specializing in geospatial analytics and computer vision

Tempe, Arizona1y exp
Arizona State UniversityArizona State University

Built and evolved a geospatial ETL + API platform that processes pixel-wise satellite imagery in PostgreSQL/PostGIS into low-latency farm-level time-series metrics for an interactive dashboard, using precomputed hotspot analysis to reduce latency by 75–80%. Experienced in FastAPI-style API contract design (OpenAPI), caching, server-side filtering/compression, and production-minded security patterns (RBAC, session-derived authorization, password hashing) with disciplined rollback/versioning practices.

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Abhishek Soni - Mid-level Full-Stack Developer specializing in React and scalable web applications in Mumbai, India

Abhishek Soni

Screened

Mid-level Full-Stack Developer specializing in React and scalable web applications

Mumbai, India3y exp
Taurus TechnologiesDr. A. P. J. Abdul Kalam Technical University

Backend/data engineer with hands-on production experience across FastAPI microservices and AWS data platforms. Has delivered serverless and Glue/EMR-based ETL pipelines with strong observability (Prometheus/Grafana/Sentry, CloudWatch/SNS), schema-evolution resilience, and measurable SQL performance wins (5 min to <30 sec). Open to onsite meetings in the Bethesda, MD area and flexible on remote arrangements.

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Harikiran Jangam - Mid-level AI/ML Engineer specializing in NLP, LLMs, and RAG systems in California, USA

Mid-level AI/ML Engineer specializing in NLP, LLMs, and RAG systems

California, USA3y exp
McKessonCalifornia Lutheran University

Backend engineer who built and evolved a PHI-compliant RAG system (FastAPI + LangChain + embeddings/FAISS) for internal document search and summarization, delivering <400ms p95 latency at ~2,500 daily requests and measurable impact (30% faster investigations, +17% retrieval relevance). Demonstrates strong security and rollout discipline (RBAC/RLS/JWT, redaction/audits, shadow mode, dual writes, canaries) and a focus on reducing hallucination risk via grounded guardrails and confidence-based fallbacks.

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Pree Simphliphan - Intern Software Engineer specializing in robotics, embedded systems, and AI in Thailand

Intern Software Engineer specializing in robotics, embedded systems, and AI

Thailand1y exp
PTTEPBoston University

Senior design robotics engineer on a "Grocery Robot" project selected for the final round of the $10K SICK Challenge, owning ROS2 system design and behavior-tree-based task orchestration across multiple independently developed modules. Also implemented I2C/ESP32 collision avoidance, IK control for a robotic arm, and a Node.js ordering system, with additional research experience using RPLIDAR-based SLAM.

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Savya Patel - Junior Mechatronics Engineer specializing in robotics, embedded systems, and mechanical R&D in Watertown, MA

Savya Patel

Screened

Junior Mechatronics Engineer specializing in robotics, embedded systems, and mechanical R&D

Watertown, MA3y exp
SharkNinjaTexas A&M University

Lead hardware/integration engineer on a high-speed autonomous drone for adversarial drone tracking and surveillance, owning the full stack from custom electronics and flight-controller tuning to ROS2 SLAM and GPU-accelerated computer vision. Built a custom USB-based ROS2 LiDAR driver and migrated SLAM from SLAM Toolbox to Google Cartographer, while boosting YOLOv5 tracking from ~2 FPS to ~45 FPS on an NVIDIA Jetson through CUDA/dependency optimization.

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SAI NAGINI VALLURUPALLI - Junior Full-Stack Java Developer specializing in Spring Boot microservices and React in Frisco, TX

Junior Full-Stack Java Developer specializing in Spring Boot microservices and React

Frisco, TX3y exp
Silicon LabsUniversity of North Carolina at Charlotte

Full-stack Java/Spring Boot + React engineer (3–4 years) who built an end-to-end smart employee management system and a data analytics dashboard handling millions of daily transactional records. Emphasizes scalable layered REST API design, secure microservices practices (Spring Security, JWT/OAuth2), and performant React state/data patterns (Redux Toolkit + RTK Query) for large datasets and role-based views.

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Sai Rahul Dasari - Mid-level AI/ML Engineer specializing in Generative AI, NLP, and healthcare RAG systems in USA

Mid-level AI/ML Engineer specializing in Generative AI, NLP, and healthcare RAG systems

USA3y exp
GE HealthCareNJIT

Built and deployed a production clinical claim validation RAG system at GE HealthCare that automated nurses’ patient-history/claims checks, cutting manual review time by ~65%. Designed the full stack (retrieval, embeddings, Pinecone, prompt/verification guardrails, FastAPI backend) with PHI-compliant anonymization via NER and orchestrated pipelines using Airflow, Azure ML Pipelines, and MLflow with drift monitoring.

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Surya Vamshi Sriperambudooru - Mid-level AI Engineer specializing in healthcare claims analytics and RAG copilots in Remote, US

Mid-level AI Engineer specializing in healthcare claims analytics and RAG copilots

Remote, US4y exp
CodoxoUniversity of Texas at Dallas

Built a production "appeals co-pilot" for a healthcare claims appeals team, combining an XGBoost/logistic ranking model with a Python/LangChain RAG stack (FAISS + Mistral 7B) to surface high-probability appeal wins and speed policy-grounded drafting. Emphasizes reliability and trust: hybrid retrieval with metadata routing, citation/eval scripts, guardrails, and an explainability layer that non-technical stakeholders could understand and override.

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Gary Chang - Senior Full-Stack Software Engineer specializing in AI-first cloud-native systems in Los Angeles, CA

Gary Chang

Screened

Senior Full-Stack Software Engineer specializing in AI-first cloud-native systems

Los Angeles, CA9y exp
System1UCLA

End-to-end engineer who has productionized AI automation and RAG capabilities, building full-stack systems (React/Node/Redis/Postgres + vector DB) with evaluation-driven quality gates and monitoring. Reported ~60% reduction in manual ops time and major turnaround improvements, and has experience modernizing legacy systems safely via feature flags and parallel runs while working across product, data, and ops teams (System1).

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Pranita Agrawal - Mid-level Software Engineer specializing in Java microservices and AWS in California, USA

Mid-level Software Engineer specializing in Java microservices and AWS

California, USA5y exp
City of ModestoWayne State University

TypeScript backend/full-stack engineer who owned an internal business workflow platform end-to-end in production, including API/data design, relational DB integration, and enterprise integrations. Has hands-on experience operating workflow processing services with Kafka-style event-driven patterns, idempotency, exponential backoff retries, dead-letter queues, and strong observability, plus API design with OpenAPI/Swagger and token-based auth.

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Nithish Nelagal - Mid-Level Software Engineer specializing in data engineering and cloud platforms in Bentonville, AR

Mid-Level Software Engineer specializing in data engineering and cloud platforms

Bentonville, AR3y exp
WalmartFlorida Atlantic University

Backend-leaning full-stack engineer who has shipped production-critical data/reporting features at Walmart and built an end-to-end workflow automation product (FastAPI + React/TypeScript + PostgreSQL) deployed on AWS. Strong in performance/reliability engineering (parallel ETL, batch DB operations, indexing via EXPLAIN ANALYZE), secure API design (JWT/RBAC), and pragmatic incident-driven scaling (separating workers from API layer).

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