Vetted Node.js Professionals

“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.”

“Full-stack product engineer who has owned complex internal platforms end-to-end, spanning React/TypeScript frontends, Flask/Redis backend systems, and relational data design. Particularly strong at turning technically dense workflows into intuitive user experiences, including a synthetic-imagery platform adopted by multiple Army research labs and a marketing analytics system with 99.99%+ uptime.”

“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.”

“Automation-focused engineer with hands-on experience building production Python integrations, maintaining 60+ Jenkins pipelines across six product lines, and hardening CI systems in real-world environments. Most notably, they turned a tribal-knowledge Windows server maintenance process into a production workflow across nine servers, saving about 500 engineering hours annually.”

“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.”

Harika M

Screened

Mid-level Full-Stack Developer specializing in FinTech and enterprise platforms

Plano, TX6y exp

“Engineer with a pragmatic, production-focused approach to AI-assisted development, using tools like Copilot and ChatGPT to accelerate coding while maintaining strict validation for correctness, security, and performance. Particularly notable for building a multi-agent incident-resolution workflow for a financial platform, with specialized agents for log analysis, root cause identification, fix suggestions, and test generation.”

Pratik Patil

Screened

Senior Frontend Engineer specializing in React and FinTech SaaS

New York, NY6y exp

“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.”

“Full-stack engineer with hands-on experience spanning React/TypeScript frontends, Cloudflare serverless RAG systems, SQL-heavy backend redesigns, and computer vision workflows. He has shipped practical automation and reliability improvements with measurable impact, including cutting a video-validation reporting process from a week to 2 days and fixing a memory-heavy shipment system before Black Friday to support 30K+ orders successfully.”

“DevOps- and infrastructure-focused engineer who is already applying AI in practical delivery workflows, including Terraform, CI/CD, Kubernetes, and multi-agent automation. Stands out for combining AI-driven productivity with disciplined validation through testing, code review, and security checks, and for leading cross-functional AI integration across development, QA, and infrastructure.”

“Built an itinerary-planning startup MVP (LessGO) using React/TypeScript and a Node/Express backend integrating Google Maps and Gemini AI. Notably optimized Gemini latency from ~40 seconds to ~3 seconds through frontend caching, debugging, and model selection, and has TA experience supporting others with deployments and database connectivity.”

Aswin Jojo

Screened

Junior Software Engineer specializing in full-stack development and machine learning

Houston, TX3y exp

“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.”

KUSHWANTH MUTHYALA

Screened

Senior Full-Stack Engineer specializing in FinTech

Irvine, CA6y exp

“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.”

Mounika Ravali Vundemodalu

Screened

Junior Front-End Developer specializing in insurance web applications

San Jose, USA3y exp

“Full-stack developer who uses AI selectively for refactoring, regex, API typing, and test scaffolding while maintaining strict manual review for security, correctness, and architectural fit. Recently shipped insurance-related features such as policy issuance and reinstatement, and demonstrated hands-on debugging of async React issues by identifying duplicate fetches in DevTools and fixing them with AbortController.”

Yogita Adari

Screened

Mid-level AI Engineer specializing in generative and multimodal systems

San Francisco, CA4y exp

“Built and productionized an agentic LLM automation system for an insurance client to determine medication eligibility, using prompt-chaining plus a RAG pipeline over policy rules and deploying on AWS (Lambda/Step Functions, Bedrock) with a serverless architecture. Addressed major data/schema mismatch issues via a semantic matching pipeline and validated performance through human agreement scoring, A/B testing, KPI monitoring, and confidence-based human-in-the-loop review.”

“Early-career engineer who built and launched a zero-to-one AI-driven approval workflow at SDSU that is used daily by roughly 2,000 university users. They owned the system end-to-end—from FastAPI/PostgreSQL backend to React UI—and showed strong judgment around LLM reliability, using a two-step pipeline, validation checks, and human-review fallbacks to cut manual processing time by about 80%.”

Bhagyashree Patil

Screened

Intern Applied AI Engineer specializing in LLM systems and data engineering

Los Angeles, CA1y exp

“Full-stack engineer with hands-on production experience across both traditional SaaS and LLM-powered support tooling. They owned a real-time ecommerce order tracking dashboard that improved support response times by 40%, and helped ship an AI support assistant using the OpenAI GPT API that cut ticket handling time by 30% through strong prompt design, retrieval grounding, validation, and human-in-the-loop safeguards.”

Pallavi Hogalagere Anandareddy

Screened

Mid Software Engineer specializing in backend systems and FinTech

Tampa, FL4y exp

“Backend/full-stack engineer with experience spanning banking implementations at FIS and hands-on product building in React, TypeScript, Node.js, SQL, and Python. Stands out for owning six bank go-lives end-to-end, building an AI resume evaluator, and proactively automating manual operations workflows to reduce errors and improve consistency.”

“Built an AI-powered document extraction system at Copart that moved from initial POC to rollout across multiple yards, with customer-driven iteration including batch processing. Has hands-on full-stack experience spanning Java/Spring Boot backends, React frontends, and LLM-based workflows, with attention to reliability through multi-LLM fallback, retries, and post-processing.”

“Backend-leaning full-stack engineer who has shipped both enterprise workflow software and AI-powered document intelligence products. Stands out for combining practical product judgment with strong production debugging skills across Spring Boot, GraphQL, FastAPI, vector search, and RAG systems, and for improving adoption by making AI search experiences intuitive for non-technical users.”

Raj Kalantri

Screened

Intern-level Software Engineer specializing in AI/ML and full-stack development

Kolkata, India1y exp

“Built a sophisticated AI career counselor as a full-stack web app for early-career students, integrating React, Flask, Pinecone, and LLM inference into a stateful conversational product. Stands out for combining hands-on debugging of retrieval/embedding pipelines with strong browser-performance instincts and pragmatic UX iteration based on real user testing.”

“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.”

“New grad software engineer with hands-on experience building production full-stack analytics infrastructure during a Swiftwise AI internship and independently shipping AI products. Stands out for combining strong TypeScript/React/backend fundamentals with practical RAG and agent-building experience, including a poker coaching assistant built solo from ingestion and retrieval through prompt tuning and evaluation.”

“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.”

“Full-stack engineer with strong banking/financial-platform experience, spanning React/Angular frontends, Spring Boot microservices, Kafka, and secure API design. They’ve built high-volume transaction systems handling 40,000+ daily requests and also owned an AI-driven search/recommendation feature that improved search relevance by 20% and adoption by 12%.”