Vetted Git Professionals

Eugeniu Cozac

Screened

Senior Frontend Engineer specializing in React/Next.js for enterprise FinTech and AI platforms

San Francisco Bay Area, CA10y exp

“Full-stack engineer with strong real-time and applied AI experience: built an internal AI “virtual subject matter expert” platform at Shell Energy serving ~1,800 employees with sub-200ms response streaming. Diagnosed AWS load balancer WebSocket disconnects and shipped reliability fixes (heartbeats, reconnect/backoff, session resume), and implemented AI production guardrails (eval suite, drift monitoring, confidence thresholds, citations, human-in-the-loop) that reportedly cut hallucinations by ~90%.”

Lizhuoyuan Wan

Screened

Junior Game Designer/Unity Developer specializing in systems and combat design

Boston, MA3y exp

“MMORPG numerical/economy designer who built and tuned a dual-currency system (gold/agate), progression gates, and late-game sinks using quantitative models (including exponential curves) and telemetry segmentation by player level/assets. Implemented engagement drivers like roguelike repeatable dungeons and weekly leaderboard rewards, and partnered cross-functionally to resolve economy risks such as item tradability to keep outputs stable and controllable.”

Mathew Martin

Screened

Mid-level Software Engineer specializing in cloud data platforms and LLM applications

New York, USA4y exp

“LLM/agent builder with experience shipping production LLM features at an early-stage ed-tech mental wellness startup (conversation analysis + structured feedback via FastAPI, OpenAI API, Render, CI/CD). Also built a multi-step dining concierge agent using OpenSearch over Yelp data with fallback query relaxation, and has enterprise data engineering experience at Capgemini migrating databases to Snowflake with robust ETL normalization and data-quality handling.”

Sushma Mangalampati

Screened

Mid-level Data Engineer specializing in lakehouse ETL and analytics engineering

Boston, MA6y exp

“Data engineer with strong end-to-end ownership of production lakehouse pipelines (Snowflake + Databricks + Airflow + dbt + Great Expectations), handling 8M+ records/month and 500K+ daily CDC updates. Delivered measurable reliability and efficiency gains (41% cost reduction, freshness improved from 4h to 30m, 35% fewer downstream incidents) and has experience building a lakehouse platform from scratch across 12 source systems.”

Vincent Chou

Screened

Mid-Level Software Developer specializing in Android frameworks and performance

4y exp

“System-level Android/Java engineer (Motorola) who owned and shipped production reliability fixes in critical services, including resolving a race condition in Android UserManagerService that allowed concurrent duplicate clone-profile creation. Strong focus on correctness, invariants, concurrency safety, and observability; ramping toward product/full-stack work (Next.js/React/Postgres) with solid architectural grounding.”

Zhiwen Zhao

Screened

Junior Data Engineer specializing in cloud ETL and big data platforms

New York, NY3y exp

“Data engineer focused on transit/transportation datasets, building Spark-based pipelines that ingest from Oracle/APIs, apply PySpark data-quality fixes, and publish star-schema fact tables to Azure Data Lake. Experienced troubleshooting complex Spark failures (using checkpointing to manage long lineage) and operating Airflow-driven backfills and GitLab CI deployments for production DAGs.”

Yash Rangucha

Screened

Mid-level Software Engineer specializing in backend microservices and real-time streaming

Illinois, USA4y exp

“Built and owned an end-to-end LLM-powered enterprise retrieval pipeline at ServiceNow, spanning ingestion of structured/semi-structured sources through vector retrieval and real-time API serving. Focused heavily on reliability and quality (multi-stage validation, monitoring, evaluation pipelines) while also driving performance improvements (~35% faster responses) via caching, async processing, and SQL/query optimization.”

Cuichan Wu

Screened

Junior Full-Stack Software Engineer specializing in scalable, AI-powered web apps

Bettendorf, IA1y exp

“Frontend-leaning engineer with production React experience and hands-on Next.js App Router patterns (Server/Client Components, Route Handlers, caching/revalidate decisions). Has built internal sales dashboards and optimized both React UI performance and SQL Server-backed analytics queries, and previously created an onboarding framework at Adobe that evolved into a configurable, multi-team reusable platform in a lean environment.”

“Built and shipped an LLM-powered support assistant for a fintech payment reconciliation system that automated failed-transaction analysis at scale. Delivered measurable production outcomes (40% less manual reconciliation, 25% better detection accuracy, 99%+ uptime) and implemented strong reliability patterns (Prometheus/Grafana monitoring, retries/fallbacks, idempotency, Resilience4j circuit breakers) plus iterative retraining driven by real error analysis.”

“Full-stack web developer with experience owning products from client discovery through launch and post-launch iteration, including a complete freelance build for an interior design firm and a large-scale React/TypeScript migration during an internship at Gateway Ticketing Systems. Stands out for balancing strong visual design with performance and SEO, and for improving emergency-use UX in an MVP product through flow simplification and A/B testing.”

“Backend engineer with strong payments and high-stakes transaction experience, including owning an Apple Pay/Google Pay integration via Stripe end-to-end in production for 100,000+ users. Particularly compelling for teams that need someone who can balance speed, security, and reliability in checkout or other sensitive backend workflows, and who has hands-on incident ownership in production.”

Vamsi Reddy

Screened

Mid-level AI/ML Engineer specializing in healthcare and financial ML systems

Nashville, TN5y exp

“ML/AI engineer with hands-on experience shipping both predictive healthcare models and clinical GenAI assistants into production. They combine strong MLOps depth across Azure and AWS with healthcare-specific safety thinking, including PHI guardrails, retrieval grounding, and production monitoring, and they also built internal Python tooling for fraud ML workflows at Capital One.”

“Backend/ML engineer who built and operated a production WhatsApp assistant end-to-end using a modern RAG stack, delivering >90% automation with sub-2-second latency. Shows strong depth in retrieval quality, observability, evaluation, and incident handling, and has also applied similar AI workflow patterns to a clinical diagnostic assistant processing medical PDFs.”

“Currently at Berryble AI, this candidate is building an LLM-based real-time interview analysis engine using FastAPI, WebSockets, fine-tuned models, and GCP/Cloud Run. They stand out for using AI and agent workflows pragmatically to accelerate development while keeping human ownership over architecture, security, reliability, and maintainability, and they are also pursuing a master's in applied machine learning.”

“ML/AI engineer with strong production depth across classical ML, MLOps, LLM/RAG, and scalable Python data platforms, with experience at Cisco and Accenture. Stands out for tying technical decisions to measurable business outcomes, including $1.2M annual savings, 40% faster support resolution, and broad internal adoption of shared engineering frameworks.”

Akhil Nakka

Screened

Mid-level Software Developer specializing in FinTech and cloud-native microservices

Remote, USA4y exp

“Full Stack Engineer in fintech (JPMorgan) who owns products end-to-end across React UIs and Spring Boot/Kafka backends, with a strong track record of shipping quickly while maintaining reliability via testing, monitoring, and feature flags. Has hands-on experience scaling microservices for high-volume transactions and debugging production latency using ELK/CloudWatch, plus built an internal Python/Flask automation tool adopted by backend engineers to speed API validation and debugging.”

“AI/ML engineer with production experience across both classical ML and Generative AI, including a real-time banking fraud detection platform at Deloitte and a RAG-based cybersecurity threat analysis feature at Accenture. Stands out for owning systems end-to-end—from feature pipelines and model tuning through deployment, monitoring, retraining, and API/platform reliability—with measurable impact on fraud accuracy, false positives, and SOC analyst efficiency.”

“Built production-scale dashboards and real-time data systems across fintech and autonomous driving, with hands-on ownership from React frontend architecture through Python/Kafka/Elasticsearch backend pipelines. At Zoox, led development of an automated safety signal attribution platform that replaced manual engineering calculations and surfaced trends through dashboards.”

Saumya Pailwan

Screened

Junior Software Engineer specializing in applied AI and audio ML

Evanston, IL2y exp

“Engineer with unusually mature experience leading AI-assisted development, including orchestrating multiple coding agents across a data pipeline feature as if managing a small engineering team. Stands out for balancing aggressive adoption of AI tools with disciplined judgment around architecture, security, and merge quality, and for translating that experience into stronger tech leadership.”

“AI engineer and current tech lead building a RAG-based multi-agent QA platform for financial document analysis at significant scale (40,000-50,000 documents). They combine Python, CrewAI, FastAPI, Hugging Face embeddings, Pinecone, and AWS SageMaker to deliver retrieval, calculation, summarization, forecasting, and visualization workflows, while leading a small cross-functional team.”

“Full-stack engineer who has owned an AI-powered HTTP monitoring dashboard end to end, from Node.js/MongoDB backend and dashboard UI through deployment and reliability controls. Particularly strong in turning raw technical signals into usable AI-assisted product experiences, with concrete impact including ~60% faster anomaly detection and meaningful AI cost optimization.”

“Candidate has built multiple zero-to-one AI/full-stack products spanning bioinformatics search, rental marketplace semantic search, and an SDR agent for a hospitality startup. Particularly strong at turning LLM/embedding concepts into usable products with modular workflows, explainable outputs, and production-minded infrastructure.”

“Frontend engineer with Oracle Cerner experience building healthcare operations UIs where accuracy, compliance, and workflow efficiency matter. They’ve owned a sophisticated React-based patient record validation and merge interface and also show solid performance instincts through render optimization, state management, and TypeScript-based API modeling.”

“Founder-owner of BoostChat who built a production AI ticket-routing platform for service businesses, bridging Telegram customer chats to contractor workflows in Revolt with measurable gains in speed and satisfaction. Also stepped from QA analyst into a lead software engineer role at Con Edison, helping modernize a legacy mapping platform.”