Vetted Next.js Professionals

“Front-end engineer with hands-on ownership of a React/TypeScript workforce management platform used by site managers and field workers in the energy sector. Stands out for building scalable, reusable UI architecture for complex task/checklist workflows while also improving real-world usability and performance through pagination, bulk actions, and close feedback loops with operational users.”

“Full-stack and AI-focused builder who has shipped both customer-facing personalization at AT&T and internal LLM-powered automation/agent systems in startup environments. Stands out for combining TypeScript-heavy engineering rigor with practical AI orchestration, evaluation, and measurable business impact—from reducing support escalation through personalization to saving 10-11 hours per week by automating fragmented operational workflows.”

Shreya Kamath

Screened

Junior Full-Stack Engineer specializing in AI-powered web platforms

San Francisco, CA2y exp

“Full-stack engineer with a strong blend of fintech and applied AI experience, having built a Stripe-based payments platform end to end and shipped an AI meeting intelligence system using LiveKit, Deepgram, and OpenAI. Particularly compelling for teams needing someone who can design reliable backend systems, productionize LLM features, and operate effectively in early-stage, ambiguous environments.”

Sai Naveen Reddy Reganti

Screened

Mid-level Full-Stack Engineer specializing in cloud-native FinTech and Healthcare systems

null4y exp

“Full-stack engineer working on customer-facing utility and banking platforms, with hands-on experience across React/React Native, Java/Spring Boot, Python/Django, AWS, and SQL performance tuning. Stands out for owning production systems end to end, improving CI/CD and deployment reliability, and delivering a measurable database optimization that cut CPU utilization from about 80% to 40%.”

Bibek Poudel

Screened

Mid-level Full-Stack Developer specializing in FinTech and E-commerce

Artesia, CA4y exp

“Full-stack engineer with experience spanning enterprise AI and e-commerce, including building an agentic orchestration platform and owning a RAG system pipeline at JP Morgan Chase. Stands out for combining React/Node backend delivery with LLM security work, RBAC-heavy system design, and practical SQL/query optimization in production.”

“Paystand engineer/intern who built a multi-agent LLM orchestration system (with logging/feedback loops) that became part of the team workflow and reportedly cut development time ~70%. Partnered with sales/product on enterprise demos and implemented a dynamic RBAC system that helped drive adoption of an intern-built product to multiple enterprise clients, contributing to seven-figure ARR. Also founded and pitched a student-entrepreneur business management/payments project (HustleHub) and won a university startup competition.”

“Product-minded full-stack engineer at a B2B startup who ships high-stakes customer-facing features fast: delivered a Spanish AI support agent in 2 weeks by benchmarking LLMs and using native Spanish system prompts, reaching 90% resolution. Built the company’s first monetization system (hybrid subscription + usage) with Stripe/Firebase, emphasizing secure JWT-based flows and idempotent webhooks, and led a microservices decoupling effort that cut developer onboarding time by 50%.”

“Backend/data engineer focused on production-grade Python microservices and AWS platforms, including a hybrid Lambda + ECS Fargate architecture managed with Terraform and CI/CD. Has hands-on reliability experience (JWT/OAuth, timeouts, retries, centralized error classification) and built AWS Glue/PySpark ETL pipelines consolidating PostgreSQL/RDS, MongoDB, and S3 sources into curated partitioned Parquet datasets. Demonstrated measurable SQL tuning impact (8 minutes to 25 seconds) and disciplined legacy-to-modern migrations with parity validation and UAT sign-off.”

“Frontend engineer in an insurance SaaS white-label environment who transformed a fragmented ecosystem of 100+ duplicated React repos into a scalable platform using versioned NPM libraries (CommonWeb/WorkflowWeb). Built a JSON-driven, multi-step quote and payment workflow in React+TypeScript with Redux-Saga for complex async orchestration and reliability (idempotency, retries, takeLatest). Delivered measurable impact: 35% bundle reduction, onboarding cut from weeks to days, and bug fixes propagated across clients in hours.”

“Full-stack engineer with financial services experience (Lincoln Financial) who owned a customer-facing financial portal end-to-end using TypeScript/React and Node/Express. Has hands-on microservices and RabbitMQ event-driven workflows, addressing scale issues like retries/duplicates with idempotency and traceable logging, and built an internal real-time ops/support dashboard to improve monitoring and incident response.”

“Software engineer with experience at Freddie Mac shipping a production workflow tracking and daily summary dashboard that replaced spreadsheet/email-based operational processes. Worked across frontend (React/JavaScript), backend (Java), Oracle relational data, and CI/CD, with emphasis on stakeholder collaboration and post-deploy testing/monitoring/performance tuning.”

“Infrastructure/operations engineer with hands-on production IBM Power/AIX (AIX 7.x, VIOS, HMC) and PowerHA/HACMP clustering experience, including DLPAR changes, failover testing, and incident recovery. Also delivers modern cloud DevOps work—GitHub Actions CI/CD for Docker-to-Kubernetes on AWS and Terraform-based provisioning of core AWS infrastructure (VPC/EKS/RDS/IAM) with controlled rollouts and drift checks.”

“Full-stack product engineer who has shipped polished customer-facing experiences across iOS (SwiftUI), web (Next.js/React/TypeScript), and Python backends. Built systems ranging from an escalating smart-reminder engine to a sub-200ms search UI over 6M+ court records, and owned AWS production operations including resolving a real DB-connection-exhaustion incident with scaling and architectural hardening.”

“Founding/solo engineer who rebuilt an early-stage product from the ground up: Ask NETA, an AI assistant for electricians to answer complex electrical code questions. Delivered a full-stack TypeScript system (React web + React Native iOS/Android, Express API, Postgres on AWS) with CI/CD, observability, and a Vertex AI RAG pipeline, reaching 3,000 MAUs in the first month; also built a real-time distributed scoring system handling unreliable hardware data with sequencing and retries.”

“Full-stack engineer with ~3.5 years of Java Spring Boot and React experience who built an end-to-end banking transaction platform using microservices, Kafka streaming, AWS RDS, and Dockerized CI/CD. Demonstrates strong performance and reliability engineering (async processing, DLQ/retries, idempotency, caching) plus secure cloud deployment practices; has also worked across banking, healthcare, and insurance domains.”

“Full-stack engineer with hands-on production experience building real-time customer-facing features (order tracking + push notifications) across React/React Native and Node/Spring Boot with Postgres/MySQL. Demonstrates strong reliability patterns (transactional outbox, background workers, idempotent webhook ingestion) and has deployed/operated systems on AWS (ECS/Fargate/ALB, CloudWatch, CodePipeline) with structured observability and environment separation.”

Gary Chang

Screened

Senior Full-Stack Software Engineer specializing in AI-first cloud-native systems

Los Angeles, CA9y exp

“End-to-end engineer who has productionized AI automation and RAG capabilities, building full-stack systems (React/Node/Redis/Postgres + vector DB) with evaluation-driven quality gates and monitoring. Reported ~60% reduction in manual ops time and major turnaround improvements, and has experience modernizing legacy systems safely via feature flags and parallel runs while working across product, data, and ops teams (System1).”

“Built and shipped production LLM agents including an AI patient appointment assistant for Kyron Medical that automated specialist matching and end-to-end booking with email/SMS confirmations and a voice mode. Strong focus on production reliability (double-booking prevention with DB constraints and pre-write checks), deterministic multi-step orchestration with LangGraph, and rigorous monitoring/evaluation using LangSmith trace replay for prompt regression testing.”

Ashish Kapoor

Screened

Director of Digital Solutions & Principal Architect specializing in composable DXP and AI transformation

Greater Philadelphia Area, USA20y exp

“Enterprise digital transformation technologist with SaaS and AI platform experience who positions themselves as a technical bridge for VC/startup contexts—focused on technical due diligence (scalability, technical debt, AI readiness) and helping portfolio companies build enterprise-grade, scalable platforms with AI-driven product development approaches.”

Medi Val

Screened

Executive technology leader specializing in AI, digital strategy, and business transformation

Toronto, Canada25y exp

“Candidate reports being highly familiar with the venture capital and accelerator landscape, citing past experience working with VC-related environments at WINR Games and BioSymetrics. The interview ended early when the candidate withdrew their application, so detail is limited.”

“Built and owned VividCraft end-to-end, a production AI platform spanning a TypeScript/Next.js frontend and a Python backend with FastAPI, Celery, Redis, PostgreSQL, and AWS. Stands out for reliability-focused systems thinking: designed idempotent job orchestration across 9 AI providers, shipped with extensive automated test coverage, and reports zero production regressions after launch plus zero credit loss through provider outages.”

“Aspiring founder focused broadly on the AI space, with no startup yet and novice familiarity with venture capital and accelerators. They are actively acclimating to the startup ecosystem through hackathons and meetup groups and express a strong all-in commitment to entrepreneurship.”

“Built a prediction market analytics website from scratch to analyze volume and correlations in decentralized markets, drawing on a sports and finance background. Shows strong early-stage product instincts, backend ownership, and a pragmatic approach to scalability, security, and AI-assisted data workflows.”

Jeremy Greenawalt

Screened

Principal AI Engineering Leader specializing in LLM integration and developer workflows

20y exp

“Built and launched a production customer-service LLM agent/MCP system for a large website, enabling reps to search across millions of SKUs and manuals that were previously impractical to navigate manually. They emphasize maintainable AI architecture, staged rollouts, guard-agent evaluation, and multi-agent code review workflows spanning accessibility, performance, and security.”