Vetted Git Professionals

“Candidate is pursuing a CTO role and has helped multiple startups turn early technology concepts into concrete, real-world technical requirements. They cite a systems science and mathematics background, along with experience at JPMorgan Chase, and appear strongest in technical strategy, concept fleshing, and identifying strong people to help teams succeed.”

“AI/backend engineer who has owned production applied-ML systems end to end, including a Jitsi meeting intelligence platform with custom RoBERTa boundary detection, LLM summarization, and automated retraining from user feedback. Also has healthcare AI experience building a diabetes medication titration system with strict validation, drift monitoring, and safety guardrails—showing both product speed and high-stakes engineering rigor.”

“Backend/product-minded engineer from Ramp with strong travel-tech experience, having built an end-to-end booking platform integrating multiple external providers, policy enforcement, and reporting infrastructure. They also shipped an LLM-powered personalization workflow using embeddings and Google Gemini that cut trip planning time by 22%, and demonstrated strong production reliability instincts through circuit breakers, health checks, and schema-driven normalization.”

“AI/LLM engineer with strong healthcare domain depth who has shipped production-grade agents for care coordination and clinical workflow automation. Stands out for combining Knowledge Graph RAG, LangGraph orchestration, and rigorous eval/guardrail systems to improve reliability in high-stakes environments, with measurable gains in review time, hallucination reduction, latency, and clinician adoption.”

Rayhaan Mohamed

Screened

Intern Software Engineer specializing in AI and full-stack development

Alpharetta, GA1y exp

“Early-career software engineer with internship experience at CirrusLabs building a voice-enabled CRM workflow that integrated Google Text-to-Speech and GPT-based processing for automated deal creation. Stands out for a reliability-focused approach to AI integrations, including validation, structured logging, prompt refinement, and hardening asynchronous API/UI behavior in real-world application flows.”

“Full-stack product engineer who has built end-to-end apps and internal tools spanning React/TypeScript, Node/Express, and Postgres. Stands out for pragmatic shipping under ambiguity, creating reusable platform primitives like a centralized notification API, and designing safe multi-tenant configurable dashboards with schema validation.”

“Product-minded full-stack engineer who has built AI-heavy systems spanning Next.js/TypeScript frontends, Python/FastAPI backends, queues, databases, and workflow infrastructure. Stands out for combining strong technical depth with UX instincts—improving trust in AI assistants, shipping ambiguous client features quickly, and creating reusable primitives for AI generation and analysis products.”

“Data engineer with a Master's in Data Science who has owned 30+ customer-facing K-12 SIS migrations end-to-end, building ETL, validation, and SOP-driven deployment processes in a PII-sensitive environment. Also brings recent hands-on agentic AI experience from a biotech capstone, where they led a production-oriented NLP-to-SQL + RAG support system that handled about 30% of support queries in testing.”

“Product-minded full-stack engineer with experience shipping engagement features and core communication systems at DribbleUp and Expys. Stands out for combining rapid MVP execution with rigorous iteration: delivered a leaderboard feature that lifted engagement by 8% initially and 20% overall, built a chat MVP in 3 days, and has hands-on experience deploying LangChain-based concierge agents with evals and human review.”

Keyan Luo

Screened

Intern-level software engineer specializing in backend and AI-powered applications

Los Angeles, CA1y exp

“Built a zero-to-one AI-powered resume tailoring platform as a personal project, owning everything from user problem discovery to frontend, backend, and AI agent architecture. Particularly strong in turning complex multi-agent AI workflows into a simple product experience for non-technical users, with a practical focus on output quality, validation, and rapid MVP iteration.”

“Frontend engineer focused on high-performance React/TypeScript applications, with detailed experience building enterprise real-time analytics dashboards and map-based geospatial visualizations. Stands out for combining strong architecture and maintainability practices with concrete production performance wins using profiling, virtualization, memoization, and backend/client data-flow optimization.”

“Full-stack engineer with enterprise banking experience at Citi and hands-on production AI agent work, including a multi-agent incident analysis pipeline using LangGraph, RAG, and LangSmith. Also built a zero-to-one healthcare operations dashboard spanning hospital workflows and AI-assisted clinical features, suggesting a blend of strong systems engineering and product-minded execution.”

PavanKumar Varkala

Screened

Mid-level Full-Stack Engineer specializing in AI-driven web applications

Jersey City, NJ4y exp

“Built and shipped an AI-driven operational workflow platform at Adobe that handled 12k+ monthly requests using React, Node.js, TypeScript, OpenAI APIs, PostgreSQL, Redis, and RAG. Stands out for combining full-stack product ownership with production-grade LLM architecture, evals, and human-in-the-loop controls, delivering measurable gains including 38% higher accuracy and 40% less manual triage.”

Keerthi Pericherla

Screened

Mid-level Full-Stack Developer specializing in cloud-native FinTech applications

Remote, USA5y exp

“Frontend engineer with HCL Tech experience building loan operations dashboards and React/TypeScript data-heavy interfaces. Stands out for combining maintainable component architecture with hands-on performance tuning, including a reported 30% load-time improvement in a production visualization-heavy application.”

Raymond Hunce

Screened

Senior Software Engineer specializing in full-stack platforms and cloud systems

New York, NY5y exp

“Frontend-leaning full-stack engineer with 5+ years of professional experience across startups and Capital One, combining UI design instincts with hands-on React/TypeScript implementation. Has owned polished browser interfaces end-to-end, built custom analytics instrumentation with DynamoDB, and improved complex internal tooling by redesigning data-heavy workflows based on direct user feedback.”

“Built full-stack features for an AI healthcare copilot at Prompt Opinion, combining React/Next.js, Node/Express, PostgreSQL, and LLM/MCP integrations over FHIR-compliant patient data. Stands out for healthcare data interoperability knowledge, production ownership, and measurable impact, including scaling chatbot throughput and improving model response accuracy by 30% through better MCP tool architecture.”

“Frontend-focused product engineer with hands-on experience designing and shipping real-time dashboards and alerting systems in regulated domains like banking and healthcare. Has led both UX/design and implementation work, combining React/TypeScript and Angular frontend expertise with Kafka-driven event architectures, performance optimization, and production monitoring.”

“Frontend-focused product engineer with experience at IBM and Intel building internal enterprise platforms, especially incentive and employee operations workflows. They repeatedly describe owning both UX/design decisions and the React frontend implementation, with strong emphasis on reusable components, API integration, and shipping ambiguous workflow products into production.”

“Built a student-focused course planning tool called Dolphin Planner and appears to have owned it end-to-end, from full-stack implementation to UX refinement. Stands out for solving a real campus scheduling problem, optimizing React rendering performance, and iterating based on direct observation of classmates using the product.”

Uma mahesh

Screened

Mid-level AI Software Engineer specializing in Generative AI and healthcare automation

NC, USA5y exp

“Backend/AI engineer with 5+ years spanning ServiceNow, Cognizant, and GE Healthcare, where they built agentic AI and RAG systems for safety-critical medical device workflows. Particularly compelling for teams needing production LLM systems in regulated environments: they combine cloud deployment and evaluation rigor with HIPAA-aware privacy controls, explainability, and measurable business impact.”

Ziyu Wang

Screened

Mid-level Full-Stack Engineer specializing in AI platforms and agents

New York, NY4y exp

“Front-end engineer focused on high-performance real-time browser applications, with hands-on ownership of an AI-integrated education platform and interactive admin tooling. Stands out for deep browser fundamentals knowledge and measurable UI performance gains, including a 40% reduction in client-side response latency.”

“Frontend engineer with strong React/TypeScript depth who built a schema-driven onboarding platform in Next.js and Apollo GraphQL to support client-specific workflows without duplicating forms. Demonstrates solid performance instincts, having diagnosed and improved lag in a production cart/order dashboard using React DevTools Profiler, memoization, debounced filters, and state isolation.”

“Unreal Engine (UE5) gameplay engineer who built large-scale open-world RPG systems end-to-end, including world streaming, AI ecosystems, and networked combat. Strong multiplayer focus: used Unreal Insights/custom profilers to identify replication/physics bottlenecks and delivered >40% frame stability improvement via relevancy checks and proxy-physics strategies, plus deterministic fixed-step simulation with rollback/state correction.”

“Platform-focused engineer/technical program leader working in silicon/wafer validation environments, with hands-on experience securing access to sensitive test results and engineering tooling. Has implemented RBAC/least-privilege controls with Azure Entra ID, Key Vault, PAM and integrated Checkmarx into dev workflows, while also deploying ML services on AKS using Bicep/Helm/Docker and Azure DevOps CI/CD with strong monitoring and incident response practices.”