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Vetted Next.js Professionals
Pre-screened and vetted.
Rethvick Sriram Yugendra Babu
Junior AI/ML Software Engineer specializing in Generative AI and scalable data pipelines
“Built and operated large-scale biodiversity/ecological research platforms, integrating 50+ heterogeneous global datasets into a unified BIEN 3 schema on PostgreSQL/PostGIS and improving data consistency by 35%. Strong production engineering background (Linux monitoring, CI/CD performance gates, Docker on AWS/Azure) plus applied AI work building a Python RAG system (0.90 precision) and halving latency with Elasticsearch.”
Varun Mahankali
Junior Full-Stack Software Engineer specializing in React, Node.js, AWS, and Generative AI
“Built and production-deployed a Streamlit-based PDF RAG chatbot using LangChain (FAISS, embeddings, prompt templates) and OpenAI, optimizing Streamlit’s stateless behavior by caching vector DB + chat history to cut latency and API cost. Demonstrates a rigorous evaluation mindset (gold datasets, unit tests, LLM-as-judge, groundedness KPIs) and has experience communicating privacy/accuracy safeguards (RBAC, data masking, citations) to a non-technical client at Kalven Technologies.”
Mayank VYAS
Mid-level AI/ML Engineer specializing in LLM agents, RAG retrieval, and IoT ML systems
“Built production LLM-driven products including a job-hunt AI (job ranking + resume optimization) and an InterviewAI agentic pipeline using LangChain. Focused on practical deployment concerns like securing OpenAI usage via rate limiting and tiered quotas, and demonstrates an applied approach to choosing models, retrieval methods (RAG), and prompting strategies.”
Atharva Chavan
Junior Full-Stack Software Engineer specializing in mobile, cloud, and GenAI integration
“Software engineering intern with hands-on ownership of a Java/Spring Boot order management microservice, including production performance tuning via Redis caching and database indexing driven by API logs/metrics. Also contributed to a production mobile-backend LLM feature using RAG with embeddings over structured data and documents (DB + object storage), with guardrails to keep responses grounded.”
Merub SHAIKH
Junior Software Engineer specializing in full-stack web development and test automation
“Full-stack engineer who built and owned a production workflow/kanban-style drag-and-drop system in Next.js (App Router) with Postgres/Prisma, including reusable component abstractions, Cypress E2E coverage, and post-launch performance/bug ownership. Notable for measurable impact (25% faster UI dev, ~30% query perf improvement) and for leading an incremental Express→NestJS migration that reduced technical debt (~40%) through better structure, docs, and team enablement.”
Ram Abhinav Vedant Madabushi
Junior Full-Stack/AI Engineer specializing in web platforms and LLM applications
“Backend engineer from FoodSupply.ai who built and evolved a scalable restaurant/supplier product and order management platform using Node.js and REST APIs. Implemented a hybrid MySQL+MongoDB data architecture, optimized performance with Redis/Prisma, and led a phased migration with feature flags and a temporary sync layer to maintain data consistency. Strong focus on production security (OAuth2, RBAC, row-level security, AWS IAM) and reliability practices (testing with Pytest, Docker/AWS pipelines).”
Atharva Bibave
Entry-level Full-Stack Software Engineer specializing in backend, cloud, and AI systems
“Software engineer with hands-on experience across platform modernization, production AI agents, and workflow automation. They led a monolith-to-microservices migration that increased deployment speed from weekly to daily, built a self-healing GPT-powered browser agent with an 85% autonomous recovery rate, and founded/ran ZapDash, where they hardened Kafka-based integrations against silent data loss.”
“Software/product engineer who has owned a consumer iOS dating app from customer discovery through roadmap execution, while also shipping an in-app LLM-powered support/feedback bot. Brings a mix of product sense and backend systems experience, including rebuilding a race-condition-prone event orchestration system and designing microservices to handle arbitrary black-box production data.”
Adam Hinton
Mid-level Full-Stack Engineer specializing in Healthcare IT and SaaS
“Backend/data engineer with healthcare/medical-device experience who scaled a HIPAA-constrained local data platform to 50k users and 1B+ records, boosting processing from <500 to ~50k datapoints/sec using sharding, indexing, and SQL over Parquet (DuckDB). Strong security and reliability focus (JWT/RLS, least privilege, heavy unit/E2E testing) and a TypeScript specialist who uses type design to eliminate edge-case failures.”
Ayushi Modi
Entry-level Software Engineer specializing in full-stack and AI systems
“Software engineer with hands-on experience spanning backend APIs, streaming data systems, and cloud/infrastructure automation, who is already using agentic AI workflows in a disciplined way. Stands out for combining practical systems work in Spring Boot, Kafka/Spark/ClickHouse, and Terraform/Kubernetes with a thoughtful approach to AI oversight, architecture, and multi-agent orchestration.”
Shayan Naqvi
Mid-level Full-Stack Engineer specializing in AI and geospatial SaaS
“Full-stack engineer in the renewable energy software space who has built an LLM-powered due diligence reader and self-serve geospatial upload workflows that materially reduced customer turnaround time. Combines Angular/NestJS product engineering with AI pipelines, geospatial data handling, and strong user-feedback-driven iteration, plus a side-project builder streak with a Spotify analytics app.”
Maksym Polinka
Mid-level Software Engineer specializing in modern frontend web applications
“Frontend-focused product engineer with strong depth in observability and real-time systems, spanning Kloudfuse and PipeIQ. They’ve built high-performance latency heatmaps and data-dense operational dashboards for large-scale telemetry, while also shaping WebSocket streaming contracts, integration architecture, and even AWS infrastructure decisions beyond a traditional frontend scope.”
kartik sharma
Mid-level Full Stack AI Engineer specializing in LLM and RAG systems
“Founding engineer and full-stack AI builder who single-handedly created Aura Groups Sweden's Trust and Growth platform across frontend, backend, ETL, and LLM services. Has hands-on experience shipping RAG-based products with OpenAI APIs and using them in real workflows, plus early-stage startup experience at nesoi.ai where they helped get an AI learning platform adopted by teams at Bain and Amazon.”
Chetan Rathore
Senior Full-Stack Engineer specializing in cloud-native web and AI-enhanced applications
“Senior full-stack developer who has operated in lean, multi-product engineering environments with significant end-to-end ownership. Strongest in JavaScript/TypeScript, React, and Next.js, with hands-on experience building a custom media player and internal business operations platforms that improved efficiency through dashboards, RBAC, search, and performance optimization.”
julian ospina
Mid-level Full-Stack Web Developer specializing in eCommerce
“Ecommerce-focused full-stack developer with broad agency and brand experience, spanning Shopify, WordPress, and BigCommerce. Most notably built a custom app to sync products and inventory across three regional storefronts with 5k+ products, significantly reducing manual duplicate work for store employees. Strong fit for roles involving custom commerce apps, B2B ecommerce workflows, integrations, and headless storefronts.”
Ned Ned Zaidi
Senior Full-Stack Engineer specializing in Python, Go, and cloud-native systems
“Full-stack/backend-leaning engineer with hands-on experience spanning Python, Go, React, Kafka, PostgreSQL, Redis, Docker, and Kubernetes. They stand out for building real-time analytics and decisioning systems, plus a healthcare-focused B2B SaaS compliance/data integration platform that combined high-throughput event processing, dashboarding, and third-party integrations in a startup-style, high-ambiguity environment.”
Hannah Aron
Senior Full-Stack Engineer specializing in Python web and cloud applications
“Full-stack engineer with strong Python/React experience who has built systems from scratch, including a custom POS platform as the sole initial engineer. They also bring applied experience across IoT reward platforms, HR matching/search systems, and LLM-powered automation products, with a track record of improving reliability and speed through thoughtful architecture decisions.”
Jookwang Jung
Staff Software Engineer specializing in AI-native platforms and full-stack systems
“Founding engineering lead and player-coach who built a small cross-functional team around an AI-first development model, increasing execution speed by more than 3x through hands-on coaching and human-in-the-loop practices. Has led architecture for a multi-tenant platform and built an AI system for fashion businesses that generates content, imagery, and operational recommendations, combining technical depth with product and UX judgment.”
Sakshi .
Senior Backend Engineer specializing in cloud-native microservices and AI backend systems
“Backend-leaning full-stack engineer who has repeatedly built web products end-to-end, including an artist booking and event management platform with complex location-based pricing, search, and booking flows. Strongest signal is ownership of backend architecture, API design, database modeling, performance optimization, and production stabilization while also partnering on frontend integration and UX improvements.”
Khushi Parikh
Junior Full-Stack Engineer specializing in AI-powered web platforms
“Full-stack engineer with hands-on experience shipping multiple AI-powered products, including donor recommendation systems, RAG-based document Q&A, and cybersecurity threat analysis tools. Stands out for combining TypeScript/React and backend API development with practical LLM evaluation, grounding, and production optimization—driving measurable outcomes like 30% higher donor engagement and 87% answer accuracy under 2-second latency.”
Darshan Shah
Mid-Level Software Engineer specializing in cloud-native microservices and full-stack development
“Full-stack engineer with deep startup experience building products from scratch under ambiguous requirements. Delivered a scalable, admin-configurable notification platform (Spring Boot/Java/Kafka) supporting 50+ notification types across 3 channels for 10k+ users, cutting new notification setup to ~5 minutes. Also built a Tinder-meets-LinkedIn job-swiping app (React/TS + Node/Prisma) and has hands-on AWS production ops (ECS/EKS, RDS, CloudWatch) plus multiple third-party integrations (Stripe, QuickBooks, Twilio).”
Alejandro Alemany
Senior Full-Stack AI/ML Engineer specializing in MLOps and GenAI
“Senior backend/data engineer who has built and maintained HIPAA-compliant, real-time clinical FastAPI services on AWS, orchestrating ML/LLM and vector DB calls with strong reliability patterns (auth, timeouts/retries, graceful degradation, idempotency). Also delivered AWS IaC/CI-CD (Terraform/Helm/GitHub Actions) across EKS/Lambda/SageMaker and built Glue/Spark ETL with schema evolution and data quality controls, plus demonstrated large SQL performance wins (15 min to <9 sec) and hands-on incident ownership.”
Tamir ShemTov
Entry-Level Computer Vision Research Assistant specializing in medical imaging AI
“New grad who shipped an LLM-powered writing app (“Write-it”) to production on Azure with CI/CD (GitHub Actions + JFrog) and implemented an unconventional RAG pipeline to prevent repetitive prompts using embeddings and cosine similarity. Also participated in a Luma AI image/video generation hackathon, iterating with artist feedback and improving usability by rewriting non-technical prompts via an LLM.”
Smit Panchal
Mid-level Full-Stack & XR Developer specializing in GenAI and immersive AR/VR systems
“Built and deployed a "personal second brain" product (CloneMind) with an end-to-end RAG pipeline for retrieving information across PDFs, URLs, images, and audio using Next.js/Node.js/Postgres/Supabase/Redis. Demonstrates strong practical depth in retrieval quality tuning, latency reduction via caching, and stateful orchestration with LangChain/LangGraph, plus experience persuading a non-technical professor stakeholder by shipping a working prototype.”