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Vetted Git Professionals

Pre-screened and vetted.

GitPythonDockerCI/CDSQLJavaScript
NK

Navya Kesani

Screened

Mid-Level Full-Stack Software Developer specializing in Java, Spring Boot, and cloud-native web apps

Lubbock, TX3y exp
Texas Tech UniversityTexas Tech University

“Former Wipro engineer who contributed to an open-source JavaScript utility library focused on frontend validation/formatting, including adding a cross-browser date-formatting module. Experienced in OSS maintenance (bug fixes, PR reviews, docs), performance profiling/benchmarking (Chrome DevTools, Node.js performance hooks), and improving community support workflows with issue templates and diagnostic logging.”

JavaPythonC++Spring BootAngularReact+62
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SK

Sudheer Kumar Divvela

Screened

Mid-level GenAI Engineer specializing in RAG, LLM agents, and enterprise automation

Louisville, KY6y exp
VSoft ConsultingUniversity of Louisville

“Accenture engineer who built and shipped a production RAG-based automation/chatbot for SAP incident triage and troubleshooting, embedding thousands of runbooks/logs/tickets into a semantic search pipeline and integrating it into Teams/Slack. Reported major productivity gains (30–60% time reduction), >90% validated answer accuracy, and sub-2-second responses, with strong orchestration (Airflow/Prefect/LangGraph) and reliability practices (guardrails, testing, monitoring).”

PythonJavaGoBashLarge Language Models (LLMs)GPT+136
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VM

Vaishnavi M

Screened

Mid-level AI/ML Engineer specializing in MLOps and Generative AI

5y exp
Liberty MutualUniversity of Maryland, Baltimore County

“At Liberty Mutual, built a production underwriting decision assistant combining LLM reasoning with quantitative models and strong auditability. Implemented a claims-based response verification pipeline that cut hallucinations from 18% to 3% and materially improved user trust/validation scores. Experienced orchestrating ML/LLM workflows end-to-end with Airflow, Kubeflow Pipelines, and Jenkins, including SLA-focused pipeline hardening.”

A/B TestingApache AirflowApache KafkaApache SparkAWSAWS Lambda+143
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NK

Neeraj Kondaveeti

Screened

Junior Full-Stack Software Engineer specializing in MERN and data/AI applications

Remote2y exp
One CommunityIndiana University Bloomington

“Early-career CS/data professional with hands-on experience integrating analytics dashboards into a production MERN system, including a Redux state redesign and schema validation that delivered zero-downtime release and measurable performance gains (~30% faster APIs, 25% faster reporting). Previously a data analyst at Reliance Jio, where they extended Python-based reporting pipelines (CSV/MySQL) with automated validation and anomaly detection to improve KPI dashboard reliability and cut investigation time by ~30%.”

AgileCI/CDC++CSSData AnalysisData Preprocessing+76
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RB

Rakshith Baskar

Screened

Junior Robotics Engineer specializing in ROS2 perception and multi-sensor calibration

Mesa, AZ1y exp
Arizona State UniversityArizona State University

“Entry-level robotics software engineer/team lead with hands-on experience spanning multi-robot UAV simulation (Gazebo + PX4 SITL) and autonomous vehicle stack integration (ROS2 Humble + Autoware Universe). Has tackled real-time perception optimization (OpenCV + custom deep learning) and built robust cross-protocol communication interfaces to connect ROS2 systems with embedded ESP32 devices.”

BashCC++Computer VisionData Structures & AlgorithmsDeep Learning+128
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KM

KrishnaVardhan Mandanapu

Screened

Mid-Level Software Development Engineer specializing in GenAI automation and cloud systems

Long Beach, CA6y exp
simplehumanGeorge Mason University

“Backend Python engineer who architected an event-driven order integration engine connecting EDI vendors to ERP/WMS/3PL systems, including a canonical order model and adapter framework to eliminate per-customer hardcoding. Has hands-on Kubernetes production experience (microservices, Celery workers, CronJobs, HPAs) and implemented GitOps/CI-CD using GitHub Actions, Docker, and ArgoCD, including moving deployments from on-prem to Azure.”

PythonJavaScriptJavaSQLFlaskVue.js+100
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SG

Saharsha Goud

Screened

Senior Full-Stack Java Developer specializing in microservices and cloud platforms

Denver, CO7y exp
DaVitaUniversity of Central Missouri

“Full-stack engineer focused on data-heavy platforms, building Spring Boot microservices and Angular/React dashboards end-to-end. Has hands-on experience improving large-scale API and UI performance (including cutting 8–10s response times) and ensuring cross-service consistency using Kafka, idempotent consumers, and strong validation/transaction patterns on AWS with CI/CD and observability (Prometheus/ELK).”

AgileAJAXAmazon API GatewayAmazon DynamoDBAmazon EC2Amazon ECS+215
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RR

Ravinder Reddy Mamidi

Screened

Mid-Level Full-Stack Engineer specializing in Java Spring Boot and React

Remote, US3y exp
SynchronyGovernors State University

“Full-stack engineer who built a cloud-native customer servicing platform at Synchrony using React 18/Next.js (SSR) and Spring Boot microservices on AWS. Experienced with high-volume, event-driven systems (Lambda/SNS/SQS) and strong distributed-systems rigor around data integrity (idempotency, DynamoDB conditional writes) plus production-grade security/observability (JWT/OAuth2, WAF, Actuator, Splunk).”

JavaCC++PythonJavaScriptTypeScript+100
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HP

Harsh Patel

Screened

Senior Data Scientist specializing in LLM applications, RAG systems, and production ML

New York, NY6y exp
Fulcrum AnalyticsUniversity of Maryland, Robert H. Smith School of Business

“Senior Data Scientist in consulting who has built production RAG systems for insurance/annuity document search at large scale (100K+ PDF pages), emphasizing grounded answers, guardrails, and low-latency retrieval. Experienced in end-to-end MLOps for LLM apps—monitoring, evaluation sets, drift handling, and safe rollouts—and in orchestrating complex pipelines with Prefect/Airflow and deploying services on Kubernetes.”

PythonNumPyPandasScikit-learnTensorFlowPyTorch+105
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AK

Amey Kore

Screened

Mid-level Robotics Software Engineer specializing in ROS, motion planning, and perception

Boston, MA4y exp
Tatum RoboticsNortheastern University

“Robotics software engineer who built a ROS/C++ workcell stack to automate coating wooden panels with a 6-DOF arm, including trajectory generation, MoveIt/OMPL planning, and a single launch/config setup that runs in both Gazebo and on real hardware. Strong in debugging real-world planning failures (e.g., intermittent aborted/no-plan regions) through logging, planner swaps, and collision/kinematics tuning, and in designing modular ROS/ROS2 systems with versioned interfaces and translation layers for heterogeneous robots.”

BashCC++CUDAComputer VisionDocker+89
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DP

Dhrumi patel

Screened

Mid-level Software Engineer specializing in Java/Spring Boot microservices

Boston, MA3y exp
IPSER LAB LLCNortheastern University

“Full-stack AI engineer who built Skillmatch AI, an LLM/RAG-based job matching platform using FastAPI microservices, Airflow-orchestrated async pipelines, and Pinecone vector search (sub-second retrieval across 50k+ vectors) deployed on GCP with autoscaling. Also partnered directly with a cancer researcher to automate SEER + PubMed-driven report generation via an AI pipeline, emphasizing rapid prototyping and outcome-focused communication.”

AgileAWSAWS GlueAWS LambdaBashCI/CD+77
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AD

Aditi Deshpande

Screened

Mid-level Software/AI Engineer specializing in GenAI, AWS, and microservices

Remote, United States4y exp
LegalPro+Arizona State University

“Built a production AI pipeline at EyCrowd to automatically grade shaky outdoor user-submitted brand videos using CV + CLIP/BLIP and a LangChain RAG layer per brand, with GPT-4 generating structured JSON explanations and grades. Optimized for latency and cost (batch PyTorch inference, caching), cutting review time from ~8 minutes to <2 minutes while reaching ~90% alignment with human graders and supporting thousands of videos/day.”

AgileApache HadoopAWSAWS LambdaBitbucketCI/CD+90
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SV

Satya VM

Screened

Mid-level GenAI/Data Engineer specializing in LLMs, RAG systems, and fraud detection

Ruston, LA7y exp
Origin BankOsmania University

“ML/NLP engineer with banking domain experience who built a GenAI-powered fraud detection and risk intelligence system at Origin Bank, combining RAG (LangChain + FAISS), fine-tuned BERT NER, and GPT-4/Sentence-BERT embeddings. Delivered measurable impact (25% higher fraud detection accuracy, 40% less manual review) and emphasizes production-grade pipelines on AWS SageMaker/Airflow with strong data validation and scalable PySpark processing.”

Generative AILarge Language Models (LLMs)Retrieval-Augmented Generation (RAG)Sentiment analysisMachine LearningDeep Learning+173
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AS

Atharva Sardar

Screened

Junior AI/Software Engineer specializing in LLM agents, RAG, and full-stack ML systems

Austin, TX2y exp
Gauntlet AIVirginia Tech

“Backend engineer who built an Emergency Alert System with Virginia Tech for the City of Alexandria, focusing on real-time ingestion, secure dashboards, and AI-assisted prioritization. Emphasizes high-stakes reliability with guardrails (hybrid rules+LLM, confidence-based fallbacks), scalable async processing, and defense-in-depth security (JWT/RBAC plus database row-level security).”

A/B TestingAgileAPI GatewayAutomationBashC+153
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EV

Eris Verne

Screened

Senior Full-Stack Engineer specializing in serverless AWS and IoT products

Los Angeles, CA8y exp
HydroPingUC Irvine

“Founding engineer with strong end-to-end product delivery across IoT + mobile + serverless cloud: built firmware for a Bluetooth-connected device (ESP32), a native Swift iOS app, and an AWS serverless backend (API Gateway/Lambda/SQS/SNS/DynamoDB) including payments via Stripe. Also shipped a separate startup product in 6 months: a React visual tool that generated HTTP/REST APIs with a Django backend, admin panel, and a code-generating CLI.”

JavaScriptTypeScriptNode.jsReactNext.jsReact Native+70
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JS

Jason Sipula

Screened

Executive Technology Leader & Strategic Architect specializing in cloud-native platforms

Sacramento, CA15y exp
Jewelry Supply, Inc.California State University, Sacramento

“Technology leader with experience driving multi-year transformations at Jewelry Supply, including migrating a legacy custom e-commerce platform to SaaS and leading a 3-year ERP program from requirements through implementation and training. Also led a major architecture shift from self-hosted virtualized infrastructure to cloud Kubernetes with a strong DevOps/DevEx focus, emphasizing stakeholder buy-in and scalable processes for distributed engineering teams.”

AgileScrumSprint PlanningCross-Functional CollaborationVendor ManagementStakeholder Communication+94
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RA

Rafael Alam

Screened

Senior Systems Engineer specializing in VR gameplay architecture and real-time AI integration

Boston, MA11y exp
LitesportParsons School of Design

“Gameplay/systems developer with shipped VR experience on Meta Quest (Litesport), owning a real-time workout scoring and progression system end-to-end including hit validation, HUD/UI, session state, and persistence. Known for event-driven architecture that decouples gameplay from UI, data-driven tunables for multiple modes, and rigorous VR performance work to hold 72 FPS using on-device profiling and debugging.”

C#C++JavaScriptUnityUnreal EngineGit+70
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SD

SRI DATTA VENGA SAMPATH VENGA

Screened

Mid-level Full-Stack Developer specializing in cloud-native web apps and AI monitoring

Fullerton, CA3y exp
Galexor AICal State Fullerton

“QA automation-focused candidate with hands-on ownership of unit and integration test suites, including CI/CD integration in GitLab. Caught a database-query regression that would have shipped incomplete API data by relying on automated integration tests, and has practical Cypress experience stabilizing flaky tests using cy.intercept()/cy.wait() and stable selectors.”

ReactTypeScriptJavaScriptHTMLCSSAngular+78
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LK

Likhith Kumar Yaramala

Screened

Junior Backend/Cloud Software Engineer specializing in microservices and DevOps

India2y exp
Brillquest TechnologiesFlorida State University

“Cloud/DevOps-focused engineer with strong Linux production operations experience, deploying microservices to AWS on Docker/Kubernetes. Has built and operated secure CI/CD (GitHub Actions/Jenkins) and Terraform IaC workflows with approvals, remote state, and drift detection, and has hands-on incident recovery experience in containerized environments; limited direct IBM Power/AIX/PowerHA exposure.”

AgileAngularAPI DesignAPI GatewayAuthenticationAuthorization+120
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ZP

Zeel Patel

Screened

Junior Backend Engineer specializing in FinTech microservices

DE, USA1y exp
TickerNortheastern University

“Backend developer (recent co-op at Ticker) building and architecting financial backend services with near real-time data needs, including third-party API integrations. Improved performance and reliability via Redis caching (tiered refresh + TTL) and PostgreSQL query tuning (EXPLAIN ANALYZE + composite indexes), and has exposure to AI-agent/RAG concepts for validating stock-market information against trusted sources.”

JavaPythonJavaScriptTypeScriptSQLSpring Boot+97
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AK

Akanksha K

Screened

Mid-Level Full-Stack Software Engineer specializing in Java microservices and React

USA3y exp
KrogerSaint Louis University

“Backend-focused TypeScript/Node.js engineer who owned a production microservice for transactional workflows in a React + microservices platform, integrating REST and Kafka event processing. Emphasizes operability and correctness (idempotency keys, exponential backoff retries, DLQs, centralized logging/metrics/alerts) plus strong API DX via versioning and Swagger/OpenAPI with improved error contracts based on developer feedback.”

JavaSpring BootSpring MVCSpring FrameworkHibernateReact+105
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PJ

prashanth Jamalapurapu

Screened

Mid-level AI/ML Engineer specializing in data engineering, LLM/RAG pipelines, and recommender systems

5y exp
FriendzySaint Louis University

“Research assistant at St. Louis University who built and deployed a production document-intelligence RAG system (Python/TensorFlow, vector DB, FastAPI) on AWS, focusing on grounding to reduce hallucinations and latency optimization via caching/async/batching. Also developed a personalized recommendation system for the Frenzy social platform and partnered closely with product/UX to define metrics and iterate on hybrid recommenders and cold-start handling.”

Anomaly DetectionAzure Blob StorageAzure Data FactoryCI/CDClassificationClustering+120
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