Vetted Node.js Professionals

Manaswini Gogineni

Screened

Junior Software Engineer specializing in cloud infrastructure and full-stack web development

San Francisco, CA2y exp

“Full-stack/platform engineer who has owned real-time analytics products end-to-end and built scalable TypeScript/React + Node.js systems using event-driven and microservices architectures (Kafka/RabbitMQ). Also created a widely adopted Go CLI that standardized AWS/Terraform provisioning across multiple teams, cutting environment setup from days to minutes through opinionated defaults, documentation, and cross-org partnerships.”

Gagan Reddy Konani

Screened

Mid-level Machine Learning Engineer specializing in LLMs and RAG for healthcare

Remote, USA2y exp

“AI Engineer (Medtronic) who deployed a production RAG-based clinical assistant grounded in curated biomedical literature (no patient-identifiable data). Deep hands-on experience orchestrating and hardening LLM workflows with LangChain/LangGraph, including stateful agentic flows, rigorous testing, and evaluation; reports a 72% accuracy improvement through retrieval enhancements (query rewriting, multi-query expansion, MMR reranking).”

“Backend/data-systems SWE (2 years) who has built production ETL/streaming workflows (Kafka, Debezium, Elasticsearch) and troubleshot real SQL performance regressions caused by indexing/type issues. Also ships full-stack personal projects in Next.js App Router + TypeScript with Postgres, emphasizing reliability via constraints, idempotency, and strong observability (Grafana/Kibana).”

“Backend/microservices engineer with fintech loan-lifecycle experience operating low-latency (sub-250ms) services in production using Kafka, idempotent transaction design, and Datadog observability. Also built an end-to-end LLM chatbot (React + Flask) with a decoupled model integration layer (FLAN-T5 via Hugging Face) and has experience designing partner-facing REST APIs with OAuth2/JWT and Swagger documentation.”

“Built and shipped a production LLM-powered multi-agent system that autonomously generates and publishes YouTube videos end-to-end (trend discovery, script writing, image/caption generation, timestamped video assembly). Emphasizes production readiness with extensive automated testing, Redis/Postgres/TimescaleDB state orchestration, and Prometheus/Grafana monitoring, reporting ~100x faster content production and improved engagement/viewership.”

Nicholas Moore

Screened

Senior Full-Stack Engineer specializing in scalable cloud-native systems

Lehi, Utah13y exp

“Backend/data engineer with production experience building high-concurrency customer engagement platforms at KomBea on AWS (EKS + Lambda) using FastAPI/Django, PostgreSQL, Redis, and strong observability. Has modernized legacy batch systems into modular Python services with parallel-run parity validation and phased rollouts, and has delivered resilient AWS Glue ETL pipelines with schema evolution and data quality controls.”

Eric Low

Screened

Principal Engineering Leader specializing in platform, product, and AI advisory

14y exp

“Fractional CTO/lead engineer who shipped an end-to-end Next.js + FastAPI product experience (login, data processing results, chatbot Q&A) with an architecture designed to support future ML model integration. Has led large-scale engineering enablement (continuous delivery across ~150 devs/200 systems), owned production incident response with lasting test/contract improvements, and delivered a 3x productivity gain by fixing debugging/tooling bottlenecks while mentoring junior teams into independent delivery.”

“Platform/infrastructure-focused engineer with hands-on experience automating AWS EKS upgrades in Python, building observability around logs/metrics/SLOs, and migrating Terraform delivery from CodePipeline to Atlantis. They describe shipping automation that handled 140 resources across 50+ Terraform files ahead of schedule and debugging a Karpenter/CoreDNS regression in Kubernetes by tracing it from regional traffic spikes to a missing local DNS cache configuration.”

Utkarsh Mittal

Screened

Mid-level Software Engineer specializing in backend and distributed systems

Murray Hill, NJ5y exp

“Backend engineer who has owned large-scale systems from design through rollout, including a Dell rearchitecture that unified two regional platforms and delivered major latency gains while scaling the effort from 6 to 150 contributors. Also built an ESG analysis product in an ambiguous startup environment using AWS Lambda, Bedrock/Claude, Flask, and custom data pipelines, showing a blend of distributed systems depth and practical AI integration.”

Jahnavi Rao

Screened

Mid-level Full-Stack Developer specializing in FinTech and enterprise web applications

Overland Park, KS5y exp

“Backend engineer currently at Bank of America with experience in scalable backend services, microservices, and event-driven systems. Stands out for using AI pragmatically as a productivity accelerator while maintaining strong engineering judgment around reliability, security, and production validation, and shows strong architectural intuition for multi-agent workflows through a distributed-systems lens.”

Abhirup Chakraborty

Screened

Junior Software Engineer specializing in backend systems, AI, and search

Champaign, IL3y exp

“Built a complex graph-based search engine to find connections between people and has hands-on experience designing multi-agent coding pipelines that move features through implementation, test generation, testing, and sanity checks. Stands out for treating AI agents like an engineering team, with shared-memory coordination, queue signaling, and completeness-focused guardrails to improve reliability and reduce ambiguity.”

“Backend/platform engineer with experience at Fidelity and PayPal, spanning financial systems, payment pipelines, and regulated AI workflows. They’ve owned large-scale deployments end-to-end, including a brokerage platform for 150,000+ accounts, and have hands-on experience integrating OpenAI into internal research tooling with compliance-safe validation and human review.”

“Senior engineering leader with over 20 years of management experience and a hands-on background leading large-scale SaaS, eCommerce, CRM, and customer data platform systems serving millions of users. Stands out for combining deep technical architecture leadership with org-scale people management, including solving multi-tenant SaaS scaling issues, driving self-service product improvements from support patterns, and building governance models for cross-functional delivery.”

“Engineering leader focused on multi-cloud platform modernization, combining deep hands-on expertise in Kubernetes, Terraform, GitOps, and DevSecOps with management of 18-person DevOps/SRE/software teams. Particularly strong in building secure, scalable enterprise SaaS infrastructure and Spark/Databricks data platforms while driving cross-functional standardization, reliability, and faster release cycles.”

“Front-end engineer with experience spanning a real-time warehouse tracking dashboard and internship work on media-heavy mobile web apps embedded in a Swift container. Particularly strong at making complex, fast-changing data understandable in the browser while preserving performance, navigation stability, and user context.”

“Senior engineering leader who scaled a global organization from 15 to roughly 100 people and operates comfortably at both executive and hands-on architecture levels. Has led SaaS platform improvements, AI-based compliance workflow automation with LLM observability, and consumer-facing product modernization using analytics-driven UX decisions.”

“Backend-leaning full-stack engineer with Amazon production experience on book and author search suggestions, plus hands-on work integrating AI agents with Node.js, Bedrock, and OpenAI Assistants. Also built internal admin tools for safety training, OSHA compliance, and digital badge workflows, showing strength in turning ambiguous operational problems into practical shipped products.”

“Full-stack builder with hands-on experience spanning a MERN e-commerce product, an AI code review agent, and an ambiguous AWS internship project involving PyTorch/TensorFlow support in Redshift. Particularly interesting for recruiters because they combine product-minded engineering with AI agent reliability work, including CI/CD integration, telemetry via Weights & Biases, and measurable impact like 80% reduction in manual review effort.”

“Built a real-time fraud monitoring dashboard in React/TypeScript for high-frequency financial data, with a strong focus on preventing UI lag that could cause analysts to miss costly fraud patterns. Demonstrates deep frontend performance expertise across batching, memoization, virtualization, profiling, and browser layout optimization, plus some graph/visualization work involving layout stabilization and edge bundling.”

“Engineering leader with a mix of people management, consulting, and hands-on architecture experience across streaming media and digital product delivery. He has built remote teams, created engineering operating models from scratch, and led pragmatic turnarounds of underperforming teams and ETL/integration systems under tight deadlines.”

Ryan Peterson

Screened

Senior Full-Stack Engineer specializing in Python web and AI applications

New York, USA8y exp

“Backend-heavy full-stack engineer with startup fintech experience who built a real-time lending eligibility service that cut decision time from 12-24 hours to under 5 seconds and lifted conversion by ~15%. Also has B2B SaaS experience automating construction workflows, with strong hands-on work across React/TypeScript, Python/FastAPI, Node.js, Kafka, Redis, and some Go.”

Carlos Morales

Screened

Director-level QA Manager specializing in AAA game testing, live services, and VR worlds

San Francisco, CA16y exp

“Game QA professional with ~5 years in embedded QA roles across major studios (Experis Game Solutions, Activision, Ubisoft, Meta), including ownership of the Weapons feature area on Ubisoft’s XDefiant and feature testing on Warzone. Known for risk-based, cross-system test coverage (matchmaking/party, progression, entitlements/MTX, performance across PC/console, live-service integrations) and for leading cross-discipline meetings and release readiness reviews.”

“ML/AI engineer with hands-on ownership of both classical ML and GenAI systems in production. They built an end-to-end churn prediction service on AWS and also shipped RAG-based document search/summarization features, with clear experience in monitoring, hallucination reduction, cost/latency optimization, and creating shared Python/LLM infrastructure used across teams.”

Garretson Beebe

Screened

Director-level Engineering Leader specializing in cloud, data, and AI platforms

San Francisco, CA17y exp

“Engineering leader with deep product-platform experience across Splunk and Alation, including owning the multi-year SPL2 initiative at Splunk from customer research and architecture decisions through execution planning and org scaling. Also grew Alation's Data Analytics organization from 8 to 22 engineers across three squads, combining hands-on technical problem solving with strong managerial systems.”