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Vetted Git Professionals
Pre-screened and vetted.
Ioannis Gregos-Mourginakis
Mid-Level Software Engineer specializing in blockchain, data pipelines, and functional programming
“Built an LLM-powered production agent that scraped X.com data to categorize and profile accounts, deployed in Docker with automatic relaunch for high uptime. Interview details were limited, but the candidate does have hands-on experience shipping an AI automation workflow.”
“Analytics-focused candidate with internship and project experience at Recotap and CoUnderscore, combining SQL, Python, and BI dashboards to turn messy marketing and engagement data into decision-ready reporting. Stands out for tying analytics work to business outcomes, including ~15% CTR improvement, identifying ~40% misattributed spend, and enabling a ~$75K budget shift through better targeting.”
“Analytics professional with Northern Trust experience focused on investment portfolio reconciliation and reporting. They combine SQL, Python, and Power BI to clean and validate high-volume financial data, automate manual processes, and align operations and accounting teams on shared metrics—driving roughly 20% improvement in reconciliation accuracy.”
Jinyao Ouyang
Mid-level Design Engineer specializing in product UX and front-end systems
“Designer-engineer who independently rebuilt the Flexi-Casa ecommerce experience end-to-end as a headless Shopify/Next.js storefront. Stands out for combining UX, frontend implementation, analytics, and A/B testing in one role, using funnel analysis to identify conversion issues and ship data-informed IA and UI improvements.”
Tahsin Nayeem Shrestha
Junior software developer specializing in data analytics and machine learning
“Entry-level software engineer who independently built an AI-powered feedback aggregation and analytics dashboard end-to-end using Cloudflare Workers, D1, and React. Stands out for combining serverless backend design, LLM-based categorization, and thoughtful UI/UX polish, with a practical approach to production debugging and data reliability.”
Chethan Thimapuram
Mid-level AI Engineer specializing in LLMs, MLOps, and healthcare NLP
“Built a production, real-time clinical documentation system at HCA that converts doctor–patient conversations into structured clinical summaries using speech-to-text, LLM summarization, and RAG. Demonstrated measurable gains from medical-domain fine-tuning (clinical concept recall +18%, ROUGE-L 0.62 to 0.74) while meeting HIPAA constraints via PHI anonymization and encryption, and deployed via Docker/FastAPI with CI/CD and monitoring.”
Robert Kennedy
Senior AI/ML Engineer specializing in LLMs, generative AI, and applied research
“Research-heavy ML/AI candidate with a PhD/publications background who translated LLM evaluation and clinical summarization techniques into production at ModMed. They owned an end-to-end healthcare GenAI pipeline that cut clinician documentation time from ~22 minutes to ~7-8 minutes, reduced token costs by ~30%, and built an internal evaluation framework later adopted by multiple teams.”
SathwikReddy Nethani
Mid-level AI/ML Engineer specializing in GenAI, NLP, and financial systems
“GenAI/ML engineer with hands-on experience building production financial intelligence and document summarization systems at Citibank. Stands out for combining LLM fine-tuning, hybrid RAG, multi-agent workflows, and strong MLOps/observability practices to deliver measurable business impact, including 60% faster analyst retrieval, 31% higher precision, and 99%+ uptime.”
Vimala Devi
Mid-level AI & Machine Learning Engineer specializing in FinTech
“ML/AI engineer with hands-on experience building production systems in financial services, including a real-time underwriting analytics platform at Hartford Financial Services. Stands out for combining classic ML, low-latency API deployment, monitoring, and emerging LLM/RAG design patterns, with measurable impact including 20% better decision accuracy, sub-200ms latency, and 5M+ records processed daily.”
Sreenitha Rayapuraju
Mid-level Forward Deployed Engineer specializing in backend systems and FinTech
“Backend-focused engineer with experience at Charles Schwab owning financial workflow deployments end-to-end, including API/database design, SQL optimization, Python automation, and AWS-based production stabilization. Also brings applied AI quality experience through building LLM/agent validation pipelines focused on scenario testing, edge-case detection, and reducing production risk.”
“Junior developer with over a year of experience who is already applying AI-assisted engineering practices in production, including GitHub Copilot, ChatGPT, SonarQube, and OpenAI-based workflows. On a Citibank public portal built with .NET 8 and Angular, they used AI tooling plus CI/CD quality gates to speed delivery and reportedly reduce post-deployment bugs by 30-40% while maintaining strict security and compliance standards.”
Tyler Moon
Mid-level Software Engineer specializing in medical device and embedded systems
“Software engineer from Abbott with hands-on experience building internal medical device engineering tools in MFC/C++/C#, including a reusable Trim Converter that automated manual workflows. Strong in modular architecture, asynchronous device communication, and iterating with users to improve reliability and workflow fit, now targeting fullstack engineering roles despite limited React/TypeScript production experience.”
“Frontend engineer with experience building specialized browser-based interfaces for asset management and machine service recommendation systems. Stands out for creating custom UI components like a calendar from scratch in pure JS/TS and CSS, while applying permission-based architecture, design-system constraints, and functional React/Redux patterns.”
Nithya Nagaraj
Mid-level Software Engineer specializing in .NET, CMS, and data visualization
“Frontend developer who helped drive a high-stakes migration from a legacy CMS-rendered UI to a code-based implementation in Visual Studio Code, acting as a POC for asset tracking and rollout coordination. They emphasize hands-on testing, QA collaboration, reusable JavaScript UI work, and cross-browser fixes, and cite a successful production launch that received positive customer feedback and internal appreciation.”
Jeffrey Ren
Mid-level Full-Stack Software Engineer specializing in SaaS and AI-enabled web applications
“Full-stack engineer who led an end-to-end rebuild of a service-agent case management app (React SPA + backend/DB updates) and added Datadog monitoring, improving agent throughput by ~1 case/hour and saving roughly $15K/month. Experienced in incremental legacy modernization (including moving a legacy React frontend toward a Rails-based approach) with heavy unit/E2E testing and strong cross-team stakeholder communication.”
Justin Stander
Staff Frontend Engineer specializing in React platforms and SaaS architecture
“Frontend engineer who owned a globally deployed, multi-brand appointment-booking experience for Estée Lauder, balancing React modernization with legacy platform constraints. Stands out for combining micro-frontend architecture, browser-performance optimization, and product analytics tools like Fullstory, NPS, and attribution tagging to drive both UX improvements and measurable revenue impact.”
Koushik Ravikumar
Mid-level Full-Stack Engineer specializing in cloud-native Java and AI platforms
“Full-stack engineer with strong cloud and platform experience spanning React, Go, AWS, Kafka, and Terraform. Has led complex migrations from monolithic/containerized systems to microservices and cloud deployments, built compliance-oriented logging infrastructure, and improved a broken frontend codebase to achieve a 3x performance gain while making it easier for other developers to extend.”
KAVYA UDATHA
Mid-level Full-Stack Java Developer specializing in retail, banking, and healthcare systems
“Full-stack engineer with hands-on ownership of a real-time retail inventory and shipment tracking platform, spanning React/Angular dashboards through Spring Boot microservices, PostgreSQL, and Kafka. Stands out for building operationally impactful systems in ambiguous environments and for thinking carefully about scalability, monitoring, and user-friendly workflow automation, even without direct production AI experience.”
Venkateswarlu Mopidevi
Mid-level Full-Stack Engineer specializing in AI and cloud platforms
“Built end-to-end product features spanning full-stack web development and LLM-powered systems in an early-stage startup environment. Notably shipped an AI financial assistant chatbot with agent routing, validation, fallback handling, and production monitoring, and also owned a scheduling system integrating Next.js, backend APIs, database design, and Google Calendar OAuth.”
Sadhana Guda
Mid-level Full-Stack AI Engineer specializing in LLM agents and RAG systems
“AI product engineer with hands-on experience shipping enterprise LLM systems at General Motors, including NL2SQL analytics, RAG-based enterprise search, and multi-agent document analysis. Stands out for combining strong technical depth in LangChain/Vertex AI/Pinecone/Redshift with disciplined evals, human-in-the-loop design, and clear business impact such as 70% to 90%+ accuracy gains, 3x analyst throughput, and rapid MVP delivery in 6 weeks.”
Nurimaro Park
Mid-level Full-Stack Engineer specializing in enterprise platforms and distributed systems
“Front-end/product engineer who has built an AI-assisted browser discussion platform combining vector-search-backed LLM responses with real-time chat, plus high-scale analytics interfaces for business users. Stands out for blending modern UI engineering with browser internals knowledge, including cross-browser extension behavior and tricky iOS Safari viewport/rendering issues.”
Nitesha Paatil
Mid-level Software Engineer specializing in backend web applications and APIs
“Backend-leaning full-stack engineer who has shipped both a SaaS analytics/A-B testing platform and an AI-driven fraud monitoring product in production. Stands out for combining React/TypeScript frontend work with Python/Java backend systems, event-driven architecture, and practical LLM integration grounded by validation and human analyst feedback, with measurable impact on engagement, performance, fraud accuracy, and false positives.”
Robert Gardunia
Staff Full-Stack Engineer specializing in AI systems architecture
“Veteran developer with 30 years of experience building unusually ambitious AI and full-stack systems, including a civic project tracker for the city of Casa Grande and multiple patent-pending AI architectures. Particularly strong in multi-LLM orchestration, agentic error-correction, and lightweight 3D/avatar experiences, with a track record of turning ambiguous ideas into working production prototypes quickly.”