Vetted React Native Professionals

Pre-screened and vetted.

Vikram Kini - Mid-Level Full-Stack Engineer specializing in React, TypeScript, and microservices

Vikram Kini

Screened

Mid-Level Full-Stack Engineer specializing in React, TypeScript, and microservices

3y exp
I-SAFE Enterprises LLCUniversity of Illinois Urbana-Champaign

Built and productionized an AI agent-based in-app assistant at ISAFE to guide users through document workflows, piloting with a partner school district and then rolling out across districts. Combines hands-on LLM/agent debugging (logs, fallback rates, state/context tracking) with strong technical demos and sales enablement through live workflows and pilot programs (e.g., Osceola School District).

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shivapriya pillalamarri - Mid-level AI/ML Engineer specializing in financial analytics and production ML systems in Boston, MA

Mid-level AI/ML Engineer specializing in financial analytics and production ML systems

Boston, MA4y exp
KenshoUniversity of New Haven

Analytics candidate with experience in financial transaction and fraud detection projects, combining SQL data preparation, Python-based automation, and dashboarding. They have owned projects from stakeholder alignment and metric definition through rollout, with emphasis on reducing false positives, improving operational efficiency, and making analytics outputs easy for business teams to adopt.

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Sangita Satapathy - Senior Full-Stack Engineer specializing in FinTech and AI applications in Las Vegas, NV

Senior Full-Stack Engineer specializing in FinTech and AI applications

Las Vegas, NV11y exp
SkillzOregon State University

Engineer with a pragmatic, production-focused approach to AI development, using tools like Copilot and ChatGPT to accelerate coding while maintaining strong engineering fundamentals. Has led a RAG-based multi-stage AI solution spanning retrieval, context building, and response generation, with an emphasis on validation, prompt quality, and reliability.

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SK

Mid-level Full-Stack Developer specializing in React, Node.js, and AI tooling

San Jose, CA6y exp
Mercedes-BenzLamar University

Frontend-leaning full-stack engineer who built internal product capabilities at Mercedes-Benz R&D, including a vehicle exploration platform, test drive booking flow, and a 0→1 vehicle comparison feature. Stands out for combining strong React architecture and performance optimization with practical backend/API ownership in Node/Express and MongoDB.

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HG

Mid-level Software Engineer specializing in AI and FinTech platforms

Seattle, WA5y exp
DreamStudioUniversity of Washington

LLM/agentic systems practitioner who specializes in moving demo-only assistants into reliable, observable, cost-controlled production services. Strong in real-time diagnosis of complex agent workflows (including tracing, loop detection, and guardrails) and in customer-facing enablement—running workshops, building tailored PoCs, and partnering with sales to close deals by proving reliability in high-risk pilots.

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Michael Zhu - Mid-level Frontend Software Engineer specializing in React and e-commerce UI in West Hollywood, CA

Michael Zhu

Screened

Mid-level Frontend Software Engineer specializing in React and e-commerce UI

West Hollywood, CA5y exp
TapcartUC Irvine

Frontend engineer with strong React/TypeScript depth who has shipped reusable CMS-driven UI architecture and improved production performance by eliminating inefficient per-component API calls. Particularly strong in maintainable component design, pagination/state management, and practical UX optimization using tools like Chrome DevTools and Theme UI.

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RG

Rohan Gore

Screened

Intern AI/ML Engineer specializing in agentic systems and full-stack development

New York City, NY0y exp
MARV CapitalNYU

Built and scaled a multi-agent LLM automation pipeline during a fintech internship, growing from a rapid 1-week proof-of-concept to a 15+ agent hierarchical system that cut market brief report generation time from ~5 hours to under 30 minutes. Hands-on with agent frameworks (Haystack, CrewAI, LangChain) and experienced in debugging agent communication issues via sandboxed modular testing and context/token management; also regularly gives architecture-first technical demos at multiple hackathons and university events.

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SG

Suraj Gajula

Screened

Junior Full-Stack Software Engineer specializing in video and security applications

Menlo Park, CA1y exp
HoneywellUC Santa Cruz

Full-stack engineer who built and owned a generative-AI pipeline end-to-end inside the Vibecut video editor using Next.js App Router/TypeScript, Gemini-based prompt routing, and Zustand state management, including concurrency-safe requests. Also integrated Python services to access newly released AI tooling, optimized Postgres/S3 data flows for thumbnails, and built Modal-to-Amplitude workflows for Reddit-driven sentiment/metrics in a pre-seed environment while also handling marketing.

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Ti Wu - Junior Full-Stack Developer specializing in web apps and reinforcement learning in Hsinchu, Taiwan

Ti Wu

Screened

Junior Full-Stack Developer specializing in web apps and reinforcement learning

Hsinchu, Taiwan1y exp
Industrial Technology Research InstituteUniversity of Wisconsin–Madison

Built an AI basketball shooting coach that analyzes player form against NBA players and recruited 30+ beta users via Reddit to drive iterative UI/workflow improvements. Also has internship experience building an administrative server and coordinating API/database compatibility with another client server, emphasizing communication and integration quality.

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AB

Junior Software Engineer specializing in full-stack, data engineering, and mobile apps

Seattle, WA3y exp
AmazonArizona State University

Built production LLM agents at Hivenue and Amazon, spanning consumer booking automation and internal data-query/reporting workflows. Stands out for combining conversational UX with strong reliability engineering—strict tool use, state machines, schema validation, idempotency, and evaluation pipelines—and can point to measurable impact including a 21% reduction in time to book and a 12% conversion lift.

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SS

Intern AI/ML Engineer specializing in full-stack and data systems

Boston, MA1y exp
ChewyUniversity of Massachusetts Amherst

Built an LLM-powered customer segmentation agent during a Chewy internship, consolidating Snowflake data into a knowledge graph so non-technical marketing users could query customer cohorts in natural language. Stands out for combining agent/tooling design with rigorous data engineering practices, including schema audits, imputation, validation layers, and idempotent pipelines on messy large-scale datasets.

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Rutuja Sanjay Risbood - Senior Full-Stack Software Developer specializing in enterprise web and mobile applications in San Jose, CA

Senior Full-Stack Software Developer specializing in enterprise web and mobile applications

San Jose, CA8y exp
Thermo Fisher ScientificUniversity of Texas at Arlington

Front-end engineer with unusually deep browser-systems knowledge, having built and owned a real-time merchant analytics platform for financial analysts handling millions of live transactions. Stands out for combining low-level performance engineering, typed React architecture, and expert-user UX polish, with strong measurable outcomes across speed, usability, and maintainability.

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JP

Mid-level Full-Stack Engineer specializing in AI, voice systems, and SaaS

4y exp
Solvr LabsUniversity of Arizona

Built Taskline end-to-end as a solo founder: an AI-native operations platform for tradespeople with web and mobile apps, AI receptionists, invoicing, scheduling, and payments. Particularly interesting for teams seeking a zero-to-one full-stack builder who can turn LLM/agent capabilities into practical, low-friction products for non-technical users.

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NC

Noah Cussatti

Screened

Junior Full-Stack Developer specializing in enterprise manufacturing SaaS

Miami, FL2y exp
QAD RedzoneRensselaer Polytechnic Institute

Frontend engineer with experience building complex enterprise web applications used by thousands of manufacturing plants globally. Stands out for pragmatic architecture decisions—especially using a BFF to tame legacy APIs and improving delivery by abandoning an overbuilt custom grid effort—while also focusing on accessibility, browser-level debugging, and regression prevention.

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RJ

Rohit Jaiswal

Screened

Mid-level Software Engineer specializing in distributed backend systems for FinTech

New York, NY5y exp
JPMorgan ChaseSyracuse University

Full-stack/backend-leaning engineer with experience spanning fintech platforms, internal AI/RAG assistants, real-time analytics systems, and a zero-to-one academic web platform. Stands out for combining hands-on backend and infrastructure work with product ownership, team guidance, and measurable impact like cutting troubleshooting lookup time from 30 minutes to under 8 minutes and creating reusable UI components adopted across multiple projects.

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GY

George Yu

Screened

Senior Full-Stack & Mobile Engineer specializing in Node.js and React

San Francisco, CA12y exp
TaskRabbitUniversidad Tecnológica de Panamá

Backend engineer with TaskRabbit experience building and operating payment/booking services in Python/Django on AWS (ECS + Lambda) with Kafka/SQS eventing. Demonstrates strong production reliability and incident ownership in high-stakes payment flows (idempotency, strict timeouts, retries, monitoring/alerting) plus data/ETL work in AWS Glue and measurable SQL performance wins.

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AK

Arda Kabadayi

Screened

Junior Software Engineer specializing in full-stack web development and computer vision

3y exp
Syracuse UniversitySyracuse University

Backend engineer who built an AI voice-driven calendar assistant using Python/Flask with a multi-agent architecture (CrewAI + OpenAI), including agent-specific memory management and summarization to handle token limits. Also has production performance optimization experience at Trendyol, adding Redis caching to speed up an advertisement retrieval endpoint and improve page load experience.

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Yijun Chen - Senior Full-Stack Software Developer specializing in IoT and cloud systems in Toronto, ON

Yijun Chen

Screened

Senior Full-Stack Software Developer specializing in IoT and cloud systems

Toronto, ON4y exp
PulsenicsUniversity of Toronto

Frontend-focused engineer who built a full movie recommendation system from concept to production, comparing classic collaborative filtering with LLM-based recommendation approaches on AWS. Emphasizes scalable architecture, strict TypeScript data contracts, and high-quality Next.js/React UI patterns (defensive states, scoped state management, performance optimization) with disciplined QA and feature-flagged rollouts.

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Abdul Mohammed - Mid-level Data Analyst specializing in healthcare and financial analytics in USA

Mid-level Data Analyst specializing in healthcare and financial analytics

USA3y exp
Cardinal HealthIndiana Tech

Built and productionized an LLM-powered clinical documentation and insights pipeline at Cardinal Health using LangChain + GPT-4 with RAG to summarize long clinical notes, extract medication/dosage entities, and generate structured SQL-ready outputs for downstream analytics. Emphasizes clinical reliability via labeled benchmarking (precision/recall/F1), shadow deployments, clinician human-in-the-loop review, and ongoing monitoring/orchestration with Airflow, Lambda, S3, Postgres, and Power BI.

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Mukul Sai Pendem - Mid-level Full-Stack Engineer specializing in cloud-native microservices and DevOps in United States (Remote)

Mid-level Full-Stack Engineer specializing in cloud-native microservices and DevOps

United States (Remote)4y exp
Saayam for AllNortheastern University

Backend engineer with strong Python/FastAPI microservices ownership, including an ML-serving service with embeddings, async DB access, and Redis caching to reduce latency under high load. Experienced deploying and operating containerized services on Kubernetes using GitOps (Argo CD/Helm) with automated CI/CD, plus hands-on Kafka streaming pipeline tuning and enterprise migration work (Infosys) using blue-green/active-passive strategies.

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KS

Ken Sherman

Screened

Executive engineering leader specializing in AI, cloud, and SaaS platforms

San Diego, CA21y exp
Executive Technical AdvisorSan Diego State University

Senior engineering executive with 8+ years leading large-scale SaaS modernization across AI, compliance, ecommerce, streaming, IoT, and travel. Has led a 150+ global engineering org, modernized seven cloud-native platforms for a $400M business, and consolidated travel systems processing $1B+ annually while staying hands-on in architecture, incident response, and AI integration.

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PJ

Senior Full-Stack Engineer specializing in distributed systems and AI-enabled platforms

College Station, TX9y exp
Texas A&M UniversityTexas A&M University

Frontend-leaning full-stack engineer with strong ownership in network observability and analytics products, including BT Group's SMARTS platform and SSpain.ai at Texas A&M. Stands out for building data-dense, near-real-time dashboards and shaping products end-to-end across React/Angular frontends, FastAPI backends, PostgreSQL, AWS, and even React Native mobile surfaces.

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Saumay Killa - Mid-level Full-Stack Engineer specializing in AI SaaS and web applications in New York, NY

Saumay Killa

Screened

Mid-level Full-Stack Engineer specializing in AI SaaS and web applications

New York, NY3y exp
HumAInorityNYU

Built a career platform feature end-to-end that generates tailored resumes and cover letters using a React/TypeScript frontend, Postgres, and AWS Lambda/SQS backend. Strong in event-driven, serverless architecture and pragmatic product iteration, with a quantified 60% improvement in onboarding completion after redesigning the UX with resume parsing and a multi-step flow.

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SP

Mid-level Full-Stack Software Engineer specializing in FinTech

New York, NY5y exp
Morgan StanleyPurdue University Northwest

Financial-services software engineer with experience building both full-stack advisor tools and production AI features at Charles Schwab. They owned an automated portfolio rebalancing workflow and helped launch an LLM-powered reporting assistant that cut report-writing time by 70%, while maintaining compliance through strict tool use, evals, and mandatory human review.

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