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Vetted Next.js Professionals
Pre-screened and vetted.
Prafull Prajapati
Senior Backend Software Engineer specializing in cloud, microservices, and AI systems
“Built an AI-powered job outreach application for his own job search and took it from idea to production use, owning architecture, FastAPI backend, retrieval/generation pipeline, frontend workflow, deployment, and iteration. Especially compelling for teams needing a pragmatic full-stack engineer who can turn LLM-based product ideas into usable, maintainable tools with measurable workflow impact.”
“Built end-to-end LLM/RAG systems for biological data and scientific literature analysis in a drug discovery setting, helping researchers explore disease insights and treatment hypotheses faster. Combines applied GenAI product work with strong production engineering, including monitoring, retrieval optimization, reusable Python services, and scalable deployment on AWS/Kubeflow.”
Pavan Kishore Ramavath
Intern Software Engineer specializing in machine learning and backend systems
“Built an AI-powered medical coding system at Clinpex that mapped 88,000+ clinical terms to standardized codes, achieving about 86% accuracy and cutting manual review time by over 80%. Brings hands-on backend ownership in a healthcare AI setting, with experience using semantic retrieval, LLM validation, and human review to handle ambiguity and reliability in a regulated domain.”
Keano Zamora
Mid-level Software Engineer specializing in backend, platform, and cloud infrastructure
“Full-stack engineer with experience owning a customer-facing data platform at GDIT, built on Django and Next.js. Demonstrated pragmatic architecture choices to handle image-heavy deployments and helped evolve the frontend from Alpine.js to a consistent React-based stack.”
SushmithaVishwanath Rao
Mid-level Software Engineer specializing in backend systems, AI automation, and SaaS
“Full-stack engineer who built and owned a production real-estate search platform (advanced search + saved-search alerts) using Next.js App Router/TypeScript with a NestJS + Postgres + Elasticsearch/Kafka backend. Demonstrated strong performance engineering (map search FPS ~20→60, ~80% latency reduction) and backend scalability (optimized alert-matching queries and orchestrated notification workflows with Airflow/Redis), with measurable post-launch engagement gains (+27% returning users).”
Aakash Khepar
Mid-level Full-Stack AI Engineer specializing in agentic AI systems
“Full-stack engineer with strong ownership across production SaaS and AI agent systems, including a multi-tenant enterprise analytics product at Fractal Analytics and an archive intelligence platform for a real nonprofit. Stands out for combining deep backend/system design, secure AI/RAG implementation, and rapid zero-to-one execution—plus multiple hackathon wins and leadership roles.”
Sai Anuhya Bandi
Mid-level Full-Stack Engineer specializing in AI-driven data platforms
“Full-stack engineer with 5+ years of experience who built real-time data visualization and analytics systems at Uber, spanning React/TypeScript frontends, Node/GraphQL services, Kafka pipelines, and PostgreSQL. Particularly compelling for teams needing a hands-on builder who can turn ambiguous customer needs into scalable products, and who has also applied RAG with LangChain/OpenAI over 1.8M support files to surface actionable insights.”
Saishyam Sundaraganesh
Executive Chief of Staff specializing in AI-enabled operations and M&A integration
“GE leader with 10 years of experience spanning software development, internal audit/consulting, and Chief of Staff leadership in GE Digital. Stood out by operating as the cross-functional execution engine for a $100M software business, driving measurable outcomes including $2.5M in AWS savings, 20% defect reduction, and $4M in audit adjustments. Combines executive-level strategy, analytical rigor, and hands-on change management across engineering, finance, legal, and security.”
Thomas Lancaster
Senior Full-Stack Engineer specializing in scalable web platforms
“Software engineer with 5+ years of experience building and scaling high-traffic web systems, including e-commerce-style purchasing/reservation flows and broker back-office platforms. He has hands-on experience across Next.js front ends, Python integrations, Go load-testing tools, and MySQL/Redis-backed architectures, with notable exposure to financial reporting, MT5 integrations, and commission logic.”
Yukta Kulkarni
Junior AI/ML Engineer specializing in applied LLMs, security, and reinforcement learning
“Built and shipped a production LLM-powered investor research feature for a fintech product, focused on grounded answers and minimizing hallucinations. Implemented retrieval-quality and evidence-coverage gating with clear refusal fallbacks, and evaluates systems with regression tests and metrics like correct-refusal rate, hallucination rate, and latency. Comfortable orchestrating workflows with LangChain or custom Python depending on production needs.”
Satya Akhilesh Pulavarthi
Mid-level Full-Stack Software Engineer specializing in FinTech and payments platforms
“Worked on payments and wallet transactions, with an emphasis on observability and root-cause analysis. Delivered end-to-end A/B testing optimization and implemented Jenkins-based CI/CD automation that reduced manual implementation to 35% and cut deployments to ~2 minutes, with attention to operational considerations like on-call/call rotations.”
Richard Cerow
Director of Marketing Technologies specializing in scalable web platforms for gaming
“Player-coach engineering leader focused on consumer-grade video/multimodal products and high-reliability identity/auth experiences. Led design and implementation of multi-step mobile login/MFA flows with telemetry-driven funnel improvements, shipped Node services and security fixes, and owned auth incidents end-to-end using RUM and step-level instrumentation. Introduced feature-flagged delivery and targeted review/testing practices to speed iteration ~20–30% while keeping login stability high.”
Pratima Singh
Senior Full-Stack Software Engineer specializing in FinTech, cloud microservices, and blockchain
“Python/ML engineer with strong DevOps depth: built an end-to-end regime-aware stock prediction system (custom fine-tuned FinBERT sentiment + technical/macro features) delivering a 12% accuracy lift. Also implemented Kubernetes/Helm + Jenkins/GitHub Actions pipelines (including GitOps-style workflows for multi-cloud Hyperledger Besu) and improved deployment speed/stability by ~50% while addressing race conditions and image drift.”
Nagarjuna Vaddineni
Mid-level Full-Stack Software Engineer specializing in cloud-native microservices and data pipelines
“Amazon backend engineer who built and operated high-scale Java Spring Boot microservices on AWS (EKS/EC2) handling millions of daily transactions, with deep experience debugging p95 latency and database/ORM bottlenecks. Shipped an AI-driven real-time personalization feature by integrating SageMaker model inference end-to-end with low-latency caching and graceful fallbacks, and designed robust order/payment orchestration with retries, compensations, and DLQ-based escalation.”
Shruti Krishnagiri
Executive Engineering Leader & Technical Founder specializing in AI automation platforms
“Founder/CTO who built and shipped a consumer subscription-bundling platform end-to-end (architecture, implementation, testing) and scaled it to thousands of customers and major partners. Previously led a major reliability overhaul at Chan Zuckerberg Initiative for a Google-Docs-like ed-tech product—boosted observability, introduced incident management, and migrated to a Docker-based scalable architecture. Heavy user of AI tools (Cursor/Claude) for development, testing, and code review, with a strong bias toward lightweight, fast-moving execution.”
Atulya Bist
Junior Data Scientist / Software Engineer specializing in LLM analytics and robotics
“Robotics/ML engineer who implemented TD3 and PPO in PyTorch to solve the challenging OpenAI Gymnasium humanoid-v5 MuJoCo task, including custom networks, rollout logic, and training scripts. Also has hands-on robotics coursework experience with ROS-based RRT motion planning on a real robotic arm, plus practical CI/CD and containerization experience (Docker, Jenkins, GitHub Actions). Currently exploring world models (VAE + sequence generator) using Euro Truck Simulator data.”
“Built and owned end-to-end production systems for a healthcare platform, including a predictive task recommendation feature (React + FastAPI + ML on AWS ECS) that cut backlog 20% and saved coordinators ~10 hours/week. Also productionized an AI-native RAG system (vector DB + LLM) delivering 40% faster query resolution, and led phased modernization of a monolithic FastAPI service into async microservices using feature flags and canary releases.”
Piyush Kautkar
Junior Software Engineer specializing in full-stack systems and distributed log analytics
“CMU candidate with hands-on experience taking LLM concepts from research prototypes toward production-ready designs (structured outputs, guardrails, failure-scenario evaluation). Also partnered with sales/customer teams at Mazecare to drive adoption with Dontia Alliance (largest dental clinic chain in Singapore) and engaged Singapore government stakeholders, bridging clinical workflow needs with IT security/integration concerns.”
Bharadwaj P
Mid-level Full-Stack Java Engineer specializing in cloud microservices across e-commerce, finance, and healthcare
“Backend-leaning full-stack engineer with e-commerce and analytics experience who modernized synchronous order workflows into a Kafka-based event-driven architecture (Java/Spring Boot) to reduce checkout latency and peak-traffic failures. Has built production FastAPI services with JWT/RBAC and strong testing/observability, delivered React+TypeScript reporting dashboards, and handled AWS scaling incidents end-to-end (RDS read latency mitigated with read replicas and query tuning).”
Alex ZhuZhou
Intern Full-Stack Software Engineer specializing in AI/LLM platforms and data systems
“Backend/LLM engineer with experience productionizing RAG systems (legal-case natural language querying) and optimizing for latency/cost, including a reported ~40% reduction via Redis caching and batching. Built monitoring and real-time debugging workflows (FastAPI, structured logging, correlation IDs, sandbox repro) and regularly delivered technical demos/workshops. Also partners with BD/sales to translate LLM capabilities into business value, including ESG-metric extraction from corporate filings.”
Bhargava Prabu Reddy Mallikarjuna
Mid-Level Full-Stack Software Engineer specializing in automation, microservices, and cloud deployments
“Full-stack engineer with experience at Apple, Walmart, and a healthcare startup (Legacy), building customer-facing PWAs and internal platforms. Delivered HIPAA-compliant clinician/patient workflows with rapid weekly releases and measurable engagement gains, and built scalable automation/testing and real-time analytics systems using Next.js/React/TypeScript, Node/FastAPI, Redis, and PostgreSQL.”
Felix Li
Intern Software Engineer specializing in data pipelines and full-stack web development
“Internship at Radar (geolocation infrastructure) where they owned automation of multiple geospatial data ingestion pipelines (including US/Canadian address ingestion), orchestrating Spark (Scala) jobs via Python-based Airflow and using GitOps-style CI/CD workflows.”
Lamar Petty
Mid-level Full-Stack Product Engineer specializing in data-driven web apps and healthcare systems
“Full-stack engineer with production experience shipping a healthcare-focused web app (Pregnancy-Pal) using Next.js/TypeScript on GCP, integrating a Python/Flask middleware and FHIR server for patient/practitioner dashboards and messaging. Former Wikimedia Foundation Android engineer who led the end-to-end 'Year in Review' feature and built robust automated testing/CI practices (Espresso, GitHub Actions matrix). Strong emphasis on reliability via rigorous validation, comprehensive Postman testing, and detailed API documentation.”