Vetted Git Professionals

“Electrical/embedded engineer who owned the end-to-end electronics and firmware for an ultra-portable desalination product at Nona Technologies, taking it from research concept through prototype, PCB bring-up, and iterative testing. Brings hands-on experience with harsh-environment hardware, mixed-voltage control systems, safety-critical monitoring, and designing consumer devices to be plug-and-play for non-technical users.”

Sai Naveen Reddy Reganti

Screened

Mid-level Full-Stack Engineer specializing in cloud-native FinTech and Healthcare systems

null4y exp

“Full-stack engineer working on customer-facing utility and banking platforms, with hands-on experience across React/React Native, Java/Spring Boot, Python/Django, AWS, and SQL performance tuning. Stands out for owning production systems end to end, improving CI/CD and deployment reliability, and delivering a measurable database optimization that cut CPU utilization from about 80% to 40%.”

Bibek Poudel

Screened

Mid-level Full-Stack Developer specializing in FinTech and E-commerce

Artesia, CA4y exp

“Full-stack engineer with experience spanning enterprise AI and e-commerce, including building an agentic orchestration platform and owning a RAG system pipeline at JP Morgan Chase. Stands out for combining React/Node backend delivery with LLM security work, RBAC-heavy system design, and practical SQL/query optimization in production.”

Manaliben Ajudiya

Screened

Senior Software Engineer specializing in cloud, .NET, and distributed systems

Mountain View, CA11y exp

“Unity developer with unusually broad applied experience spanning real-time face recognition, AR geospatial systems enhanced with LLM-driven interactions, multiplayer networking, and cross-platform VR/mobile delivery. Also owned Honeywell Guided Work Solutions end-to-end, building server and client applications across web, Windows, and mobile for frontline worker workflows.”

“Full-stack product engineer with hands-on ownership from UX/design collaboration through React frontend build, FastAPI/Django services, and AWS deployment. Particularly notable for shipping AI-powered customer support experiences using RAG, LangChain, OpenAI, and Pinecone in a banking context, while also showing pragmatic MVP execution on inventory management workflows.”

“Full-stack and AI engineer with Capital One experience spanning real-time customer dashboards and production fraud-analysis systems. They combine TypeScript/Next.js/Node.js product engineering with LangChain-based RAG architecture over a 400 GB credit-report corpus, delivering measurable impact including 35% lower frontend latency and 45% faster analyst workflows.”

“Built and shipped both a full-stack AI-assisted school planning product and an OpenAI-powered VS Code extension for translating code comments safely in multilingual codebases. Stands out for combining TypeScript-heavy product engineering with pragmatic LLM reliability work like masking, validation, structured outputs, regression testing, and human-in-the-loop design.”

“Robotics software engineer focused on multi-robot fleet orchestration in ROS 2, owning the fleet manager and task dispatch layer for pick/drop workflows. Strong in real-world reliability and safety (heartbeats, idempotent tasking, E-stop/localization confidence gates) and in debugging timing/state issues via telemetry alignment and rosbag replay, with experience in simulation, CI/CD, Docker, and Kubernetes-based deployments.”

“Product-minded full-stack engineer at a B2B startup who ships high-stakes customer-facing features fast: delivered a Spanish AI support agent in 2 weeks by benchmarking LLMs and using native Spanish system prompts, reaching 90% resolution. Built the company’s first monetization system (hybrid subscription + usage) with Stripe/Firebase, emphasizing secure JWT-based flows and idempotent webhooks, and led a microservices decoupling effort that cut developer onboarding time by 50%.”

“Backend engineer from Optum who built and optimized a real-time, Kafka-driven healthcare claims processing platform handling 1M+ claims/month. Strong in reliability, state management, and observability for distributed systems, plus production deployment automation with Docker/Kubernetes and CI/CD; no direct ROS/robotics simulator experience yet but frames work in robotics-adjacent real-time principles.”

“Robotics-focused engineer with hands-on projects ranging from a solo Dobot Magician Lite tic-tac-toe system (computer vision + minimax) to integrating an LLM with a Dobot arm for real-time pick-and-place via structured action outputs and validation. Also brings prior full-time DevOps experience (Docker/Kubernetes and CI/CD) and has used ROS/Gazebo for simulation work, including exploring improvements to crowd-aware navigation using human-trajectory datasets.”

“Built and deployed a production LLM-powered workflow assistant that automated internal marketing/production business tasks (document summarization, repeated Q&A, status updates). Demonstrates end-to-end applied LLM engineering: modular RAG architecture, hallucination/latency mitigation, automated evals to prevent prompt regressions, and Azure-based orchestration (Functions/Logic Apps) with monitoring and controlled rollouts.”

“Built and deployed a production LLM-powered RAG assistant for healthcare teams (care managers/support) to answer questions from clinical and policy documentation, emphasizing trustworthiness via improved retrieval, reranking, and strict grounding prompts to reduce hallucinations. Also has hands-on orchestration experience with Apache Airflow for end-to-end ETL/ML workflows and applies rigorous testing/metrics (hallucination rate, tool-call accuracy, latency, cost) to ensure reliable AI agent behavior.”

“Backend/data engineer focused on production-grade Python microservices and AWS platforms, including a hybrid Lambda + ECS Fargate architecture managed with Terraform and CI/CD. Has hands-on reliability experience (JWT/OAuth, timeouts, retries, centralized error classification) and built AWS Glue/PySpark ETL pipelines consolidating PostgreSQL/RDS, MongoDB, and S3 sources into curated partitioned Parquet datasets. Demonstrated measurable SQL tuning impact (8 minutes to 25 seconds) and disciplined legacy-to-modern migrations with parity validation and UAT sign-off.”

“Early-career engineer from BNP Paribas who drove a large-scale observability modernization—selecting and implementing Prometheus/Grafana for a 2000+ server estate, then productionizing it on Kubernetes via Docker/Jenkins. Known for hands-on demos, strong documentation/templates, and pragmatic troubleshooting (including custom Python metrics) that improved visibility and cut debugging time by ~60%.”

“ML/AI engineer with healthcare payer experience (Signal Healthcare, Cigna) who has shipped production fraud/claims prediction systems using Python/TensorFlow and exposed them via FastAPI/Flask microservices integrated with EHR and Salesforce. Emphasizes operational reliability and trust—Airflow-orchestrated pipelines with data quality gates plus SHAP-based interpretability, A/B testing, and drift/debug workflows—backed by reported outcomes of 22% lower false payouts and 17% higher model accuracy.”

“LLM/agentic systems engineer who built a production "Agentic AI Diagnostic Assistant" for network engineers, using a multi-agent Llama 2 + LangChain architecture with RAG over telemetry/incident data in DynamoDB and confidence-based deferrals to reduce hallucinations. Also has strong MLOps/orchestration experience (Airflow, EventBridge, Spark, Docker, SageMaker/ECS) at multi-terabyte/day scale and delivered multilingual NLP analytics (fine-tuned BERT/spaCy) for support operations through hands-on stakeholder workshops.”

“Software engineer/product owner experience at UnitedHealth Group owning a high-volume claims eligibility console end-to-end (React/TypeScript + Spring Boot microservices) processing 1M+ transactions/day. Strong in event-driven architecture (Kafka/RabbitMQ), HIPAA-aligned security (OAuth/JWT/RBAC), and building internal observability tools that improve incident triage and production reliability.”

“Full-stack engineer with financial services experience (Lincoln Financial) who owned a customer-facing financial portal end-to-end using TypeScript/React and Node/Express. Has hands-on microservices and RabbitMQ event-driven workflows, addressing scale issues like retries/duplicates with idempotency and traceable logging, and built an internal real-time ops/support dashboard to improve monitoring and incident response.”

“Significant contributor/maintainer to an open-source JavaScript event-tracking client SDK, owning API consistency/backward compatibility, high-load batching and retry/backoff improvements, and test/CI + documentation upgrades. Diagnosed production-like issues (missing events under load) via reproduction and logging, then reduced GC pressure and improved predictability with a ring-buffer-based batching redesign while actively triaging issues and reviewing PRs.”

“Full-stack engineer with production experience building Java 17 Spring Boot microservices for high-traffic systems at Verizon and on a JPMC payments platform (funds transfer/validation using ISO 20022), plus modern React/TypeScript dashboards for ops and analytics. Demonstrates strong scalability and reliability chops (Kafka event-driven pipelines, Redis caching, clustering, BullMQ background jobs) and has built real-time apps end-to-end with secure JWT refresh-token auth and Socket.io performance tuning.”

“Backend/DevOps-leaning engineer with trading/financial systems experience (AIG), focused on reliability: built Python automated test suites to ~95% coverage and integrated them into CI/CD. Has hands-on Kubernetes microservices deployment with GitOps (ArgoCD), plus experience supporting cloud-to-on-prem migrations and building real-time streaming pipelines resilient to spikes and data loss.”

“Backend/platform engineer with hands-on ownership of high-stakes data migrations in regulated domains (core banking and insurance), including a Python ETL framework that migrated 100,000+ customer records within a cutover window. Strong DevOps/GitOps background deploying Python and Spring Boot microservices to Kubernetes with Helm and ArgoCD, plus real-time Kafka transaction streaming for fraud/analytics with reliability patterns (DLQs, retries, partition tuning).”

“Backend/ML engineer who built an end-to-end greenwashing detection system for corporate ESG reports: Python preprocessing pipeline, logistic regression + fine-tuned DistilBERT models, and a Dockerized FastAPI inference service optimized for latency. Internship experience maintaining GitLab CI/CD for TypeScript services (Jest/Playwright), improving pipeline stability and test determinism; familiar with Kubernetes/GitOps concepts and AWS CLI/SSO.”