Vetted Node.js Professionals

“Built and deployed a production RAG-based internal document Q&A system using LangChain, vector search, and a dockerized FastAPI LLM service. Focused on reliability by systematically reducing hallucinations and improving retrieval through prompt grounding/abstention strategies, chunking and top-k tuning, and iterative evaluation with logged metrics and manual validation.”

“Backend Python engineer who owned a real-time manufacturing insights streaming service, building FastAPI async microservices with Kafka-style queue buffering, batching/backpressure, and a low-latency snapshot store. Led a serverless-to-Kubernetes (EKS) migration at UGenomeAi using GitOps-style GitHub Actions pipelines, standardized config/secrets, and improved deployment consistency with pinned dependencies and multi-stage Docker builds.”

“Application-focused engineer who has shipped end-to-end products across mobile and web, including a music-based dating app feature for sending searchable/previewable songs in chat and a geospatial events service integrating external APIs. Demonstrates strong product + engineering instincts: performance-minded PostgreSQL modeling, Dockerized deployments with env-based config, and UX/accessibility polish backed by user studies, plus hands-on incident mitigation using Vercel logs.”

“Full-stack system analyst/programmer at PeakPlay Sports (startup) who built an AI "coach" product end-to-end in ~2 months, using a LangGraph-orchestrated multi-agent architecture with a FastAPI backend. Shipped production RAG grounded in athlete history (OpenAI embeddings + vector store) with guardrails and a structured eval loop (golden set + LLM-judge + human review) to improve engagement and reduce hallucinations.”

“Full-stack developer who owned and shipped an end-to-end web application for LeafNBeyond (React/Node/Postgres), deployed to production at leafnbeyond.com, with reported 35% sales growth and strong UX feedback. Also built Azure-based ETL pipelines using lakehouse/medallion architecture with validation and retry logic, and has AWS fundamentals from a master’s coursework (EC2, RDS, IAM, load balancing).”

“Student full-stack builder shipping real products: a mobile app (Sirat) where they delivered end-to-end theme settings with testing and fast post-launch fixes, and a sports web app (Scorva) that generates AI game summaries from game stats with Postgres-backed caching to control LLM costs. Available for full-time work starting June 2026 and targeting $95k–$110k.”

Diego Torres

Screened

Mid-level Mobile Front-End Developer specializing in React Native apps

Anzoategui, Venezuela3y exp

“Mobile/frontend engineer with hands-on ownership of major app initiatives, including migrating a telecom app from Ionic to React Native using an MVVM architecture and Jest unit testing. Built complex airline app experiences in React + TypeScript (booking, seat maps, Stripe payments) and improved maintainability by replacing a complex Redux-like booking flow with a simpler Context-based system; experienced working both as a solo mobile developer and within Agile teams using Jira/Notion.”

Venkata Bayarapuneni

Screened

Junior Full-Stack Developer specializing in JavaScript, Python, and cloud-deployed web apps

Remote, USA1y exp

“Built and deployed a production LLM-powered travel assistant (Globe Trote) that automates end-to-end trip planning using a multi-step agent pipeline with RAG, external API calls, and enforced structured JSON outputs. Focused on reliability (validation, retries, fallback prompts, logging) and reported a ~30–40% reduction in irrelevant/generic responses after adding retrieval grounding.”

“Built end-to-end product features for a Web3 monetization platform and also shipped a privacy-first mobile accessibility app, SenScribe, using on-device sound classification and LLM summarization with zero cloud dependency. Particularly interesting for roles spanning full-stack product engineering, mobile AI, and applied ML where careful debugging, stakeholder alignment, and real-world usability matter.”

“Builder with hands-on experience shipping full-stack products across AWS cloud infrastructure, React/TypeScript apps, SQL-backed systems, and privacy-focused AI workflows. Stands out for combining cost-aware architecture, strong debugging instincts, and product thinking—from an e-commerce platform automated with IaC to a university admin portal serving 10,000+ users and a locally run AI assistant with configurable guardrails.”

“Robotics software engineer with ROS 2 Humble/Nav2 experience on a warehouse robot fleet, focused on improving throughput in dynamic human environments. Implemented C++ local-planner and velocity-control changes using LiDAR-based motion prediction and real-time costmap tuning under a 20ms control loop, and built a Gazebo digital twin with custom failure-injection plugins plus Docker/Kubernetes deployment tooling.”

“Built a university campus assistant chatbot (BabyJ/WWJ) using RAG and agentic routing with a FastAPI + React stack and JWT auth, focusing heavily on production concerns like latency and reliability. Uses techniques like speculative prefetching, smart intent routing, and rigorous eval/testing (golden sets, regression, edge cases) while collaborating closely with campus admin/advising teams to iterate based on real user feedback.”

“Software engineering intern who built and deployed a full-stack telemedicine platform (React/Node/MongoDB) used daily in a pediatric clinic, incorporating PyTorch-based predictive features. Demonstrated strong customer-facing iteration and production performance debugging—resolved a live slowdown by indexing/optimizing MongoDB queries and adding caching, improving response times by ~50%.”

“Full-stack engineer at Srasys Inc. who built and owned production payments/checkout for an e-learning platform serving 5,000+ users using Next.js App Router + TypeScript. Deep focus on correctness and reliability (Stripe webhooks, signature validation, DB-level idempotency) plus measurable performance wins (~40% latency reductions) through Postgres indexing/EXPLAIN ANALYZE and Redis-backed caching with CloudWatch monitoring.”

“Built and shipped production AI features in the automotive dealership domain, including an end-to-end computer-vision damage detection system for trade-ins and a tool-calling, RAG-enabled LotSync AI Agent that answers inventory/VIN questions using strict schemas and internal APIs to avoid hallucinations. Also developed a Dagster + Oracle automated reporting pipeline as a Graduate Research Assistant, supporting 15+ university departments with normalized, reliable ETL workflows.”

Yousef Abdelsalam

Screened

Junior Software Engineer specializing in Odoo, web performance, and backend systems

Orlando, FL2y exp

“Full-stack developer who shipped LLM-powered customer support automation, including an AI call center designed for always-on, high-concurrency real-time phone handling. Also built a WhatsApp lead-conversion chatbot using Zapier webhooks, Redis state, and Twilio messaging, and reports measurable outcomes (+11% customer satisfaction, ~7% cost reduction) while using GPT-4.1.”

Wilson Huang

Screened

Junior Backend & Full-Stack Engineer specializing in Python/FastAPI and cloud services

Binghamton, NY4y exp

“Robotics software contributor from Binghamton University’s drone research lab who built a Dockerized, multithreaded Python control stack integrating Crazyflie firmware for low-latency, real-time coordination of multiple drones. Hands-on with telemetry/command pipelines, profiling and control-loop optimization, and wireless comms using CrazyRadio PA.”

Ayushant Khandekar

Screened

Junior Full-Stack Developer specializing in GenAI-powered web and mobile apps

Remote2y exp

“Web3 creator-led growth and community builder who frames crypto as infrastructure and designs content to drive measurable on-chain behavior. Uses X-native distribution (threads, replies, quote-tweets) paired with interactive CTAs and on-chain dashboards to convert attention into trust and product usage, with a structured 90-day plan for launching and scaling protocol communities.”

“Built and shipped production LLM-driven pipelines for clinical data processing, turning semi-structured inputs into validated structured outputs for downstream analytics. Emphasizes predictability and safety via strict JSON schemas, state-machine orchestration, backend-controlled tool calling, and robust fallbacks (rule-based checks/manual review) plus monitoring and offline/online evaluation loops; also has experience hardening workflows against messy ERP/finance data with idempotency and state tracking.”

Citlalli Trejo

Screened

Entry-level Full-Stack Developer specializing in web, iOS, and ML applications

Buena Park, CA1y exp

“Builder-minded software engineer who has shipped a live iOS budgeting app and a solo full-stack web app, with strong evidence of production discipline in both ML and fintech-style integrations. Particularly compelling for roles involving ambiguous product problems, third-party API reliability, and end-to-end ownership from backend logic through user-facing recovery flows.”

“Early-career software engineer who has already owned a real-world web product end-to-end for a 100+ member university ACM organization, including requirements gathering, UI/UX improvements, hosting, CI/CD, and ongoing maintenance. Brings hands-on React and full-stack project experience with a strong bias toward practical execution, mobile-friendly design, and reliable delivery.”

“Built and shipped a production AI assistant for a web-based loan/interest calculator that helped users understand EMI results and optimize inputs. Demonstrated full-stack ownership across responsive UI, Node.js APIs, and LLM integration, with a strong focus on prompt refinement, guardrails, caching, fallbacks, and post-launch iteration driven by logs and user behavior.”

Abhay Bisht

Screened

Junior Software Engineer specializing in AI and full-stack SaaS

Bangalore, India2y exp

“AI-first developer who reports using agents for roughly 85% of coding work, with a disciplined process centered on detailed specs, prompt design, review, and testing. Has built a personal multi-agent orchestration setup with specialized agents for testing, PR extraction, review, and synthesis, and stays current through AI engineering newsletters and a network of AI companies.”

“Backend/ML engineering candidate focused on fintech automation who architected a zero-to-one agentic/LLM-enabled system to reconcile messy financial documents and bank transactions, reporting ~40% operational efficiency gains. Experienced migrating monoliths to event-driven microservices with incremental rollout via reverse proxy, and implementing production-grade security (OAuth2/JWT, RBAC, Supabase RLS) plus resilience patterns (timeouts/retries under concurrency).”