Vetted React Professionals

Pre-screened and vetted.

SK

Sangeeth Kumar Mohan

Screened ReferencesModerate rec.

Senior Lead Software Engineer specializing in authentication platforms and distributed systems

15y exp
T-MobileLincoln University

Full-stack engineer (T-Mobile experience) focused on authentication/session-management systems, with hands-on work optimizing token-validation flows and reducing latency by eliminating redundant API calls and adding caching. Brings strong production ownership with observability (Splunk/Grafana), Postgres data modeling/index tuning, and resilient async workflow design (idempotency, retries/backoff, queues).

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Khaliun Gerel - Senior Full-Stack Engineer specializing in cloud, web, and mobile platforms in New York, NY

Khaliun Gerel

Screened ReferencesStrong rec.

Senior Full-Stack Engineer specializing in cloud, web, and mobile platforms

New York, NY7y exp
GertechColumbia University

Full-stack product engineer who has owned end-to-end delivery of multi-client platforms: Finy (agriculture platform with 3 role-based web dashboards plus 2 field mobile apps) and Ugoku (Japanese studio platform with React/TypeScript dashboards, Node/Mongo backend, and mobile AR video playback). Strong in scalable architecture and performance—offline-first mobile for low connectivity, and AWS-based asynchronous video/AR processing with S3/CloudFront—plus building internal ops tools adopted quickly due to measurable workflow improvements.

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Osaze Edo-Osagie - Senior Frontend/Full-Stack Engineer specializing in React and TypeScript in New York, USA

Osaze Edo-Osagie

Screened ReferencesStrong rec.

Senior Frontend/Full-Stack Engineer specializing in React and TypeScript

New York, USA7y exp
MeltwaterUniversity of Nottingham

Frontend engineer from Meltwater who led delivery of a universal post details modal used across multiple apps, integrating three different frontend frameworks (Vue, React, StencilJS) into a plug-and-play StencilJS feature. Built scalable, reusable UI components and even helped create an internal CSS library/design system, with a strong focus on performance optimization and reliable QA-driven rollouts.

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LX

Longyang Xu

Screened ReferencesStrong rec.

Junior Full-Stack Software Engineer specializing in cloud microservices and ML-driven products

Quincy, MA1y exp
GraniteCarnegie Mellon University

Backend engineer with hands-on ownership of Python/Flask microservices and recommendation systems across edtech and telecom. Deployed and operated real-time personalization/recommendation platforms on AWS EKS with Jenkins-based CI/CD, GitOps-style declarative configs, and strong observability practices. Has migration experience moving legacy mixed environments to modern containerized Kubernetes and built Kafka pipelines feeding ML services while managing schema evolution.

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Mark Connolly - Director-level UX and design systems leader specializing in enterprise platforms in Remote, USA

Mark Connolly

Screened ReferencesStrong rec.

Director-level UX and design systems leader specializing in enterprise platforms

Remote, USA28y exp
Parasol ProjectsMassachusetts College of Art and Design

Frontend architecture leader with deep browser-platform expertise who led the UI for Fidelity's next-generation account optimization platform and built a framework-agnostic web component ecosystem before Fluent existed. Particularly strong in semantic component design, event-driven architecture, performance tuning at scale, and highly disciplined testing, with recent hands-on work in GIS/map-based visualization prototypes.

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YS

Yoga Sathyanarayanan

Screened ReferencesStrong rec.

Junior Software Engineer specializing in backend, distributed systems, and AI infrastructure

New York, NY3y exp
NYU Stern School of BusinessNYU

Full-stack engineer with hands-on experience spanning real-time AI products, large-scale payments migration, internal research infrastructure, and open-source ML tooling. Particularly compelling is the mix of low-latency React/Node/TypeScript systems work, zero-downtime migration of 50,000 accounts across 12 regions, and proactive contributions to Kubeflow build and security reliability.

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Sreenaina Koujala - Mid-level Full-Stack & AI Engineer specializing in cloud and intelligent systems in Ashburn, VA

Sreenaina Koujala

Screened ReferencesStrong rec.

Mid-level Full-Stack & AI Engineer specializing in cloud and intelligent systems

Ashburn, VA8y exp
Zazvata Inc.George Mason University

Builder with experience across government contracting, engineering automation, and solo AI product development. They architected a serverless AWS pipeline that converted unstructured BIM data into IFC 3D models, built an enterprise internal-data chatbot with auditability and guardrails at Steampunk, and independently launched an AI study platform using Claude. Strong fit for early-stage or ambiguous environments where end-to-end ownership and practical AI systems matter.

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MM

Senior Software Engineer specializing in AI/ML backend and cloud infrastructure

Bentonville, AR11y exp
WalmartUniversity of Houston

Backend/data platform engineer with production experience at Walmart and Molina Healthcare, building Python microservices on AWS (EKS + Lambda) for real-time inventory and recommendation systems. Strong in reliability/observability and incident leadership, plus modernizing legacy healthcare workflows and building resilient AWS Glue/PySpark pipelines with schema evolution and data quality controls.

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HM

Junior AI/ML & Cloud Software Engineer specializing in LLM applications

2y exp
Randomwalk.AIUniversity of Illinois Urbana-Champaign

AI engineer (2+ years; pursuing an online MS at UIUC) who has shipped an AI-powered voice screening platform end-to-end on GCP with strong production monitoring and measurable hiring-process impact (80% reduction in unqualified pass-through; ~50+ hours saved per role). Also built and deployed an AWS-based context-aware hybrid search system using OpenSearch as a vector store, and has hands-on experience with multi-agent LLM orchestration (ReAct) and structured-output guardrails.

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SC

Mid-level Data Engineer specializing in cloud data platforms and real-time streaming

5y exp
Vertisage TechnologiesCarnegie Mellon University

Worked on onboarding a Middle East logistics client processing thousands of invoices/month, building a production-ready pipeline that routes known vendor PDFs to deterministic regex parsers via Tax ID matching and falls back to LlamaParse for unknown layouts. Added financial consistency validation plus human-in-the-loop review and logging/metrics to continuously reduce LLM usage and improve template coverage.

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Ajith P - Mid-level Backend Software Engineer specializing in AI workflow automation for finance and healthcare

Ajith P

Screened

Mid-level Backend Software Engineer specializing in AI workflow automation for finance and healthcare

4y exp
Goldman SachsUniversity of Central Missouri

Backend/AI engineer with healthcare domain experience who built a patient journey analytics API (FastAPI/PostgreSQL/Snowflake/Redis) and debugged peak-hour latency down from ~900ms to ~50ms via indexing and query optimization. Shipped an LLM-powered clinical summary/recommendation assistant end-to-end and designed a multi-step risk evaluation agent workflow with safety guardrails against hallucinations and unsafe outputs.

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Daniel Jeong - Junior Full-Stack Engineer specializing in real-time platforms and AI tools in Cambridge, MA

Daniel Jeong

Screened

Junior Full-Stack Engineer specializing in real-time platforms and AI tools

Cambridge, MA3y exp
DraperColgate University

Early-career full-stack engineer with unusual depth in mission-critical environments: helped build a cybersecurity operations platform from scratch as the third engineer and shipped it to the National Election Commission of South Korea. Also worked on defense-focused situational awareness software, combining React/WebGL frontend performance work with backend data transformation for real-time weather and map overlays.

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JR

Jugal Rayala

Screened

Mid-level Full-Stack Developer specializing in AI-powered cloud applications

Remote, USA5y exp
MicrosoftWebster University

Full-stack engineer who has owned customer-facing AI recommendation and analytics dashboards end-to-end (backend APIs/data processing through React UI, deployment, and monitoring). Demonstrates strong systems thinking around scaling microservices—using observability, caching, async workflows, and resilience patterns—and also built an internal ops dashboard that became the default tool for on-call incident reviews.

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DY

David Yoo

Screened

Junior AI Solutions Engineer specializing in enterprise LLM systems

Frisco, TX2y exp
WorldLink USCornell University

Recent Cornell graduate with roughly 18 months of unusually high-impact Solutions Engineering experience, already owning enterprise AI engagements for Citi and Samsung at WorldLink US. Stands out for combining technical pre-sales with hands-on prototyping and delivery, including local on-device AI for Samsung QA and helping take an AI security product from architecture to first $100K close.

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MG

Megan Gwynne

Screened

Executive product leader specializing in e-commerce, marketplaces, and growth

San Francisco, CA21y exp
For Goodness SakeUC Davis

Senior product leader with experience spanning luxury e-commerce and consumer education, including leading personalization and AI-driven shopping experiences at The RealReal and serving as Chief Product Officer/strategic product consultant at OMGYES. Stands out for combining ML-powered product strategy, strong UX judgment, and cross-functional leadership to deliver measurable business impact, including conversion and revenue gains at scale.

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DT

David Toth

Screened

Senior Software Engineer specializing in backend APIs and regulated industries

Austin, TX10y exp
HumanaUniversity of Texas at Austin

Software engineer with recent hands-on production work across Go, Python, and React/TypeScript, spanning healthcare APIs, compliance systems, and data engineering. Stands out for delivering under ambiguity: replaced a legacy SOAP eligibility service, built a Kafka-based compliance pipeline handling 14,000 events per second, and created a modular banking data pipeline that cut month-end work by 30%.

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JC

Jenny Cheng

Screened

Junior Full-Stack/ML Engineer specializing in LLM applications and cloud deployment

Remote, USA1y exp
MetaUC Irvine

Full-stack developer with capstone and project experience delivering production-ready systems in unstructured environments, including a Faculty Tracking system for real departmental use. Strong in React performance debugging (re-render optimization with useMemo), Prisma-backed multi-database setups (MySQL local / SQL Server production on a UCI Health VM), and end-user support workflows that feed back into improved Help documentation.

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VK

Senior Software Engineer specializing in Cloud, Zero Trust, and Enterprise Platforms

San Jose, CA13y exp
CotivitiSanta Clara University

Zero Trust security product lead focused on UI/API delivery, stability, and customer adoption at enterprise scale, including deployments serving 1200 customers. Stands out for hands-on production debugging across the full stack, customer-facing incident ownership, and a pragmatic approach to turning failures into automated regression coverage.

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MM

Principal Applied Scientist specializing in ML systems and Generative AI

Tampa, FL11y exp
OracleUniversity of South Florida

Built and owned an end-to-end agentic RAG chatbot platform for Baptist Health that helped clinicians access policy and clinical documents faster, reducing manual lookup by 80% and delivering about $2M in annual savings. Brings strong healthcare GenAI production experience, including HIPAA-aligned governance, PHI redaction, observability, evaluation, and scalable Python/Kubernetes deployment practices.

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Praneeth Regonda - Mid-level Full-Stack Engineer specializing in FinTech and AI platforms in New York, NY

Mid-level Full-Stack Engineer specializing in FinTech and AI platforms

New York, NY4y exp
BloombergPace University

Full-stack engineer with 3 years of AI/ML experience who has shipped production LLM workflows, including a Bloomberg triage dashboard that cut manual processing by 35%. Combines React/TypeScript product sense with AWS/Spring/Lambda backend architecture and unusually strong practical judgment around evals, trust, retrieval, latency, and UX for real-world AI systems.

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TG

Junior Software Engineer specializing in full-stack AI systems

Greenwich, CT1y exp
Birdie AICornell University

Sole developer behind BirdieAI, an AI-powered golf booking platform built from the ground up, spanning frontend UX, backend services, AWS infrastructure, and Postgres database management. Worked directly with a cofounder in a startup setting to scope and ship an MVP, then improved production reliability significantly by reducing a key extraction failure from 1 in 15 to 1 in 300 while adding operational safeguards and user-driven product improvements.

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MM

Meet Merchant

Screened

Mid-level Software Engineer specializing in LLM agents and full-stack systems

Redlands, California3y exp
EsriUC Irvine

At Esri, the candidate is building a production LLM-powered WebGIS AI framework that embeds an AI assistant into web maps and routes natural-language requests into ArcGIS JavaScript SDK functions via a LangGraph-orchestrated, multi-agent system. They emphasize production reliability and scale (strict tool calling/JSON, live schema validation, query guardrails) and rigorous evaluation/observability using LangSmith, offline prompt datasets, and latency/tool-call accuracy tracking.

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MN

mahesh narne

Screened

Senior Full-Stack Software Engineer specializing in cloud-native microservices and web apps

San Jose, CA3y exp
PayPalUniversity of Central Missouri

Backend-focused engineer building customer support/order-tracking platforms with Java 17/Spring Boot microservices and a React/TypeScript frontend. Deep experience running event-driven systems on Kubernetes (Kafka, Redis, MySQL) with strong observability (Prometheus/Grafana/Splunk), SLOs, and safe deployment practices (feature flags, canaries). Also built an internal monitoring/debugging dashboard that consolidated metrics and logs for on-call engineers and was adopted by other teams to speed incident response.

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