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Vetted Next.js Professionals
Pre-screened and vetted.
Andre Kuznetcov
Staff Front-End Engineer specializing in high-performance web apps and AI products
“Frontend engineer who built uichallenges.design end-to-end in Next.js, delivering hourly AI-generated challenges across timezones and a CDN-backed gallery of 1k+ items while staying fast for 100s of weekly active users. Also led a full replacement of Zenhub’s kanban board, forking DnD tooling and adding custom virtualization + Redux to support thousands of items with real-time socket updates, shipped safely via gradual rollout with Sentry/Mixpanel and A/B testing.”
Apurva Banka
Mid-level Full-Stack & AI Engineer specializing in cloud, data platforms, and LLM automation
“Software engineer/product builder who has owned an agentic affiliate lead-gen platform end-to-end (Django + React/TypeScript) and deployed it on Kubernetes in anticipation of 10x user growth from ~5K DAUs. Also has healthcare claims microservices experience using Kafka, including hands-on performance tuning to address consumer lag and broker pressure, and built an internal downtime alerting tool adopted across the organization.”
Vedang Jadhav
Mid-Level Software Engineer specializing in cloud-native microservices on AWS
“Backend engineer with experience across healthcare and fintech platforms (Anthem, Citia) building high-throughput Python microservices with strong compliance/security focus (HIPAA, tenant isolation). Has integrated ML workflows into production systems (ResNet embedding-based image similarity) using async pipelines (Celery/Redis) and AWS (Lambda/S3/ECS), delivering measurable performance and fraud/content-integrity improvements at scale.”
Tina Nguyen
Mid-Level Software Engineer specializing in iOS and full-stack development
“Cross-platform (web + mobile) product engineer working on coupon clipping experiences. Built and shipped category-based filtering informed by external market data (Rakuten/Honey) and internal user-journey analytics, validated via A/B testing and resulting in a 30% traffic lift. Experienced handling on-call production incidents, including rapid root-cause analysis and hotfixing a mobile crash that was blocking a release.”
RAJ KUMAR
Mid-level Full-Stack Software Engineer specializing in FinTech and cloud-native microservices
“Backend engineer at Discover who built and scaled Python/Flask services for a card dispute resolution platform, tackling long-running external network validations with Celery+Redis and delivering measurable gains (response time ~3s to <300ms; throughput +40%). Experienced in high-scale PostgreSQL/SQLAlchemy optimization (partitioning, read replicas, N+1 avoidance), event-driven systems with Kafka, and integrating ML fraud detection using AWS SageMaker/Lambda/ECS with clear separation of real-time vs batch processing.”
Madhu Sriram Sengottu Velan
Entry-Level Software Engineer specializing in backend systems and distributed services
“Backend/AI engineer from an early-stage Japan-based startup (WorkAI) who built a multi-tenant RAG system integrating Notion/Slack/Google Drive with Pinecone and OpenAI, including a chatbot retrieval workflow. Experienced in production reliability (rate limits, retries, verification layers), strong Python/FastAPI engineering practices, and PostgreSQL performance optimization; currently based in India and needs sponsorship.”
sudha kumari
Senior Full-Stack Product Engineer specializing in Next.js, TypeScript, and distributed systems
“Full-stack engineer who built and shipped an analytics dashboard for search visibility using Next.js App Router/TypeScript with a server-components-first data strategy and server actions for interactivity. Designed and optimized the underlying Postgres analytics model and queries at scale, and implemented a durable Temporal-based indexing workflow with retries and idempotency—plus delivered a major frontend performance jump (Lighthouse low 70s to mid-90s).”
Ali Taquie
Junior Software Engineer specializing in AI and FinTech payments
“Forward-deployed software engineer at PayStand who uses LLM prototyping tools (e.g., Cursor, Lovable) to rapidly build customer-specific demo environments and drive sales outcomes—citing ~$100K in technical buy-in before production development. Experienced supporting an enterprise expense management product (Teampay) with agentic AI workflows, emphasizing observability (Grafana/Loki/Tempo) and cross-functional communication with sales, product, developers, and customers.”
Teage Johnson
Junior Full-Stack Engineer specializing in FinTech and machine learning
“Software engineer at early-stage startup Cari with hands-on experience shipping AI-enabled production workflows, including an LLM chatbot for a micro-transit platform and an automated image-processing pipeline integrated with Claude. Stands out for combining practical agent reliability patterns—schema validation, fallbacks, caching, and idempotency—with strong ML evaluation instincts and experience cleaning messy operational invoice data.”
Ajay Kancheti
Mid-level Full-Stack Engineer specializing in SaaS and FinTech
“Product-minded full-stack engineer focused on internal operations tooling, with hands-on ownership across React/TypeScript, serverless APIs, and Postgres. They combine UX simplification with deep performance and reliability work, citing a transaction-exception workflow redesign that cut task completion time by roughly 25%, and they’ve also built multi-tenant configurable systems with strong guardrails.”
Wyatt Fong
Entry-level Full-Stack Software Engineer specializing in AI and healthcare tech
“Built a Python pipeline to monitor and classify public posts from sources like Hacker News and Reddit for SWE/tech job opportunities, with a strong focus on reliability, observability, and recoverable failures. Also currently building a court queueing system for the UCSD Badminton Club, showing an ability to turn messy, informal real-world processes into practical automation through iterative user feedback.”
Hari Banchode
Senior Software Engineer specializing in microservices and FinTech/e-commerce platforms
“Full-stack engineer with end-to-end ownership of a production customer plan activation and account management flow at T-Mobile, spanning Java/Spring Boot APIs, React frontend, and Docker-based CI/CD deployments. Demonstrated performance/scalability work (query optimization, indexing, caching) and measured success via improved retrieval speed and reduced support tickets.”
Pratik Patil
Senior Frontend Engineer specializing in React and FinTech SaaS
“Senior engineer at BDI Plus who is already using AI coding tools as a core part of daily development, with hands-on experience building enterprise LLM products such as ChatCDP AI for Morgan Stanley analysts. Particularly strong at making AI systems trustworthy and usable through auditable outputs, streaming UX, and resilient state-machine-driven error handling.”
Aswin Jojo
Junior Software Engineer specializing in full-stack development and machine learning
“Full-stack engineer with experience owning products end-to-end in both insurtech/financial workflows and AI-enabled IT operations. Built scalable React/Node and FastAPI systems, improved reliability under peak transaction load with SQS/Redis, and shipped an AI ticket-classification platform that cut response times from 3 days to 1 day.”
“Engineer with hands-on experience building and deploying end-to-end ML inference pipelines using SageMaker, TensorFlow, Scikit-learn, and Kafka-backed real-time data systems. Brings a strong distributed-systems mindset and has already operated in a tech lead capacity through architecture decisions, code reviews, and cross-functional coordination. Especially compelling for teams building production AI/ML platforms that need both practical execution and sound engineering judgment.”
Bismanpal Anand
Entry-level Software Engineer specializing in distributed systems and agentic AI
“Full-stack and AI product engineer who has shipped both operational SaaS and LLM-powered research tools to production. Built a dispatch optimization system at Quickflora that cut manual effort by ~50%, and also developed grounded RAG and agentic systems using tools like LlamaIndex, Gemini, pgvector, and FastAPI with a strong emphasis on citations, reliability, and practical user workflows.”
Kanav Chopra
Senior Front-End Engineer specializing in React, TypeScript, and healthcare AI
“Frontend-focused engineer building production-grade, browser-based AI products, including a live clinical decision support platform for Stanford clinicians. Stands out for combining sophisticated React/TypeScript streaming UI architecture with strong browser performance expertise, including Core Web Vitals and rendering-pipeline optimization.”
Shejal Shankar
Mid-level Full-Stack Engineer specializing in AI and real-time systems
“Full-stack engineer who shipped a production "Financial Insight" assistant dashboard in Next.js App Router/TypeScript, integrating a RAG pipeline (embeddings + ChromaDB + LLM) via route handlers and owning post-launch performance (latency, token cost, retrieval relevance). Also built/optimized Postgres-backed workflows for an outbound dialer and callback routing engine handling ~10,000 daily contacts, validating query performance with EXPLAIN (ANALYZE, BUFFERS).”
Sandeep Reddy
Mid-level Software Engineer specializing in full-stack cloud-native systems
“Full-stack engineer with hands-on experience building real-time analytics and logistics platforms across modern JavaScript and Java stacks. They combine strong production ownership and database optimization skills with architectural leadership, including redesigning bottlenecks with SQS/Lambda and driving a monolith-to-microservices migration on Kubernetes that cut deployment time by 50%.”
Vincent Willliams
Senior Python Backend Engineer specializing in scalable APIs and cloud-native microservices
“Backend/data platform engineer who has built and operated a cloud-native media ingestion/processing platform in Python (Django/DRF, FastAPI) with Kafka, Postgres, and Redis, emphasizing multi-tenant security and reliability. Delivered AWS production systems combining EKS and Lambda with Terraform + GitHub Actions/Helm, and built Glue-based ETL pipelines with strong schema-evolution and data-quality practices; also modernized SAS analytics into Python on AWS. Seeking fully remote roles with a $120K–$140K base range.”
Aaron Lao
Intern Software Engineer specializing in agentic RAG and full-stack web development
“Entry-level software engineer who built an agentic AI backend in Python/FastAPI, including APIs for conversation history retrieval and user data storage, and worked through async/concurrency challenges for multiple agents querying simultaneously. Also has practical AWS experience using S3 for static hosting with Lambda and RDS for backend/data access.”
Alfred Fox
Senior AI/ML & Full-Stack Engineer specializing in GenAI, RAG, and MLOps platforms
“Backend/data platform engineer who owned end-to-end production services for a fleet analytics/GenAI platform, spanning FastAPI microservices on Kubernetes and AWS (EKS + Lambda) event-driven workloads. Strong in reliability/observability (OpenTelemetry, circuit breakers, idempotency), data pipelines (Glue/Airflow/Snowflake), and measurable performance/cost wins (SQL 10s to <800ms P95; ~30% compute cost reduction).”
Sol Lee
Mid-level Full-Stack Developer specializing in web apps, APIs, and React/TypeScript
“Frontend engineer who has led React + TypeScript products end-to-end, emphasizing scalable architecture (custom hooks, compound components) and quality via strict typing, CI, and code review standards. Experienced shipping complex multi-step workflows with strong performance practices (virtualization, code splitting, RUM) and de-risked rollouts using feature flags, monitoring, and rapid iteration in collaboration with product/design.”
Shree Gopalakrishnan
Entry-Level AI/ML Engineer specializing in LLM apps, RAG pipelines, and production ML systems
“AI/LLM practitioner at iFrog Marketing Solutions who drove a RAG chatbot from prototype to production in a legacy, AI-resistant environment by validating customer needs and building a business case. Implemented production-grade LLM practices (CI/CD eval gating, rollbacks, prompt/context engineering) and led internal workshops to bring non-AI-native developers up to speed while partnering with sales on tailored demos to drive adoption.”