Vetted React Professionals

Pre-screened and vetted.

JS

Johnnie Sanders

Screened ReferencesModerate rec.

Executive AI Architect specializing in enterprise cloud and FinTech solutions

Lewisville, TX15y exp
11-11 Solutions Ent.Purdue University

Candidate brings an operator-to-founder profile with leadership experience in IT and Business Systems and a strong grasp of how ideas become venture-backable products. They speak fluently about startup evaluation criteria such as TAM, technical defensibility, speed to scale, and AI differentiation, and appear especially motivated by building solutions end-to-end in startup or venture studio environments.

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Dhananjay Sharma - Mid-level Full-Stack Engineer specializing in AI and FinTech platforms in Stony Brook, NY

Dhananjay Sharma

Screened ReferencesModerate rec.

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

Stony Brook, NY6y exp
State University of New York - Research FoundationStony Brook University

Full-stack engineer who built RegArt’s product from 0→1 for enterprise compliance users at clients like HSBC and EY, including the production React frontend, backend APIs, and an LLM-powered search experience. Particularly compelling for startups needing someone who can move across UI, API, and data layers, make pragmatic architecture tradeoffs, and ship fast without over-engineering.

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KS

Kshitij Singh

Screened ReferencesModerate rec.

Intern Software Developer specializing in healthcare data and systems analysis

Telangana, India0y exp
Apollo HospitalsIIT Jodhpur

Candidate comes from SaaS and healthcare analytics rather than game development, but has strong end-to-end ownership experience building real-time, high-availability systems in Python/AWS. They highlight measurable impact across performance, throughput, uptime, and cost reduction, including queue optimization and predictive ICU utilization pipelines, and are looking to transfer that systems engineering foundation into Unity/gameplay work.

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HD

Harbir Dhillon

Screened ReferencesModerate rec.

Mid-level Software Engineer specializing in distributed systems and cloud-based full-stack development

Stockton, CA3y exp
California Health Care FacilityVanderbilt University

Software engineering candidate who built a compiler-like Python tool to translate between Python code and UML-style diagrams (and back). Also has hands-on AWS experience building a distributed pub/sub system using services like Lambda, API Gateway, ELB, WAF, VPC, and DynamoDB, plus ML projects using Kaggle datasets (e.g., diabetes risk analysis).

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Vaughn Eugenio - Mid-Level Software Engineer specializing in distributed microservices and real-time systems

Vaughn Eugenio

Screened ReferencesModerate rec.

Mid-Level Software Engineer specializing in distributed microservices and real-time systems

2y exp
DraftKingsUniversity of South Carolina

Software engineer with production experience at DraftKings and SRC, owning high-impact platform changes like early-start lineup validation fixes and a multi-service refactor to support dual-role players (e.g., Ohtani) using backward-compatible, feature-flagged rollouts. Has embedded onsite with military users to rapidly ship improvements to a COP/TAK mapping integration (TrackSync), and leverages AI tools (Claude) to accelerate learning and delivery in new domains (e.g., ESP32 smart deadbolt project).

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NK

NEHA KOLAN

Screened

Mid-Level Software Engineer specializing in microservices and cloud data pipelines

Texas, USA4y exp
CignaUniversity of North Texas

Full-stack engineer with end-to-end ownership across React/TypeScript frontends, Spring Boot/Node microservices, and production ops on Docker/Kubernetes and AWS (ECS/CloudWatch). Built real-time healthcare eligibility and analytics systems at Cigna and an early-stage seller onboarding platform at Flipkart, driving measurable performance gains (35–40% latency/throughput improvements) through event-driven Kafka pipelines, Redis caching, and strong reliability/observability practices.

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SS

Saffinah Shi

Screened

Junior Software Engineer specializing in full-stack, cloud serverless, and AI systems

Los Angeles, US2y exp
CoreSpeedNorthwestern University

SDE who worked on an MGICS Lab robotics project building a multi-agent model to help agents understand tasks and generate robot instructions, emphasizing task-splitting, checking, and a reflection agent to improve accuracy. Also has experience using GitHub with automated CI/CD pipelines.

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CC

Caden Cheah

Screened

Intern Full-Stack/ML Engineer specializing in LLM applications and mobile development

Los Angeles, CA1y exp
IlloominateUC Berkeley

Backend engineer who built a serverless AWS Lambda microservices backend for a parenting assistance mobile app, including a personalized recommendation system optimized to sub-500ms via precomputed scoring and DynamoDB caching. Demonstrates strong production pragmatism: CloudWatch-driven performance tuning (provisioned concurrency), zero-downtime phased schema migrations, and robustness patterns like optimistic locking and request deduplication. Also led a refactor of an LLM RAG pipeline to improve retrieval quality and cut latency from ~5s to ~3s.

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CN

Mid-Level Software Engineer specializing in Java, Spring Boot, and AWS

USA4y exp
Progress SolutionsUniversity of Michigan

Built and deployed a production credit card fraud detection platform that scores transactions in real time using TensorFlow/scikit-learn models exposed via a Spring Boot REST API, with strict SLAs, fallback to legacy rules, and Splunk-based monitoring/drift tracking. Also has enterprise orchestration experience with TIBCO BusinessWorks (BW 6.6/BWCE), coordinating REST/SOAP services and JMS messaging (TIBCO EMS) with robust error handling and compensation logic.

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KM

Mid-Level AI/ML Software Engineer specializing in agentic LLM systems

Dallas, Texas6y exp
DatatronUniversity of West Florida

Built and deployed a production LLM-powered multi-agent compliance copilot (life sciences/finance) using LangChain/LangGraph + RAG over vector databases, delivered via async FastAPI on Kubernetes. Emphasizes audit-ready, deterministic outputs with schema constraints and citations, plus rigorous evaluation/monitoring; reports 60%+ reduction in manual research time and successful production adoption.

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MP

Michelle Poon

Screened

Senior Front-End Engineer specializing in React and TypeScript

Remote, Canada8y exp
Leonardo.AiCarleton University

Frontend engineer with senior-level scope who has shipped complex React/TypeScript products end-to-end, including a multi-page site built solo in four weeks (complex forms, PDF generation, email + localization) and a GraphQL-driven dashboard for a car dealership management platform. Known for modular, testable architecture, performance-minded data fetching (batched calls), and improving design-system consistency via reusable, Storybook-documented components and feature-flagged rollouts.

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SS

Mid-Level Full-Stack Software Engineer specializing in API-first microservices and cloud platforms

Arlington, TX4y exp
University of Texas at ArlingtonUniversity of Texas at Arlington

Backend-focused engineer who built a resume processing and job application platform using Python/MongoDB/Streamlit, including OpenAI-powered skill/keyword extraction and recruiter-facing search/filtering. Has hands-on cloud deployment experience on AWS/Azure and executed an on-prem reservation portal migration to Azure using a phased trial-and-cutover approach; also automated CI/CD with Jenkins and GitHub Actions.

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HT

Hassam Tariq

Screened

Mid-Level Software Engineer specializing in Cloud, GenAI, and Federal systems

Arlington, VA
DeloitteUniversity of Maryland, College Park

Cloud-focused engineer experienced deploying and stabilizing complex production systems that span APIs, infrastructure, and automated workflows, with a strong observability and safe-release mindset (feature flags/canaries/rollbacks). Has hands-on, customer-facing incident leadership, including executing DR regional failover during an AWS us-east-1 outage to maintain service and reportedly save a client ~$10M.

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OB

Omkar Bhope

Screened

Staff Full-Stack Engineer specializing in AI platforms and infrastructure automation

San Jose, CA5y exp
Etched AIUC San Diego

Backend/full-stack engineer building complex internal platforms and customer-facing demos at the intersection of infrastructure and product. Shipped a no-code Product Lifecycle Manager for manufacturing (3 manufacturers, 1000+ evolving tests) using AWS S3/SQS ingestion and extensible Postgres (EAV+JSONB) with end-to-end traceability. Also built a FastAPI-based company data intelligence platform with Okta-secured RBAC and an LLM/MCP layer for ChatGPT-like analytics over enterprise data sources.

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SB

Silpa Bhavani

Screened

Mid-level Full-Stack Java Developer specializing in cloud-native microservices

Oakland, CA5y exp
BlockLamar University

Software engineer with strong compliance-domain experience who built a customer-facing compliance and reporting dashboard using React/TypeScript with Spring Boot microservices. Demonstrates mature production engineering practices—contract-first APIs, event-driven architecture (Kafka/RabbitMQ), caching (Redis), and robust CI/CD + observability (Prometheus/Grafana/ELK)—and also created a Python-based audit automation tool adopted into the standard release process.

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TK

Mid-level AI/ML Engineer specializing in Generative AI, RAG, and Conversational AI

3y exp
AetnaIndiana Tech

Built a production RAG-based GenAI copilot backend at Aetna using Python/FastAPI, GPT-4, LangChain, and Azure AI Search, deployed on AKS with Prometheus/Grafana observability. Owned the system end-to-end (ingestion through deployment) and improved peak-time reliability by addressing vector search and embedding bottlenecks with Redis caching, index optimization, and async processing, plus added anti-hallucination guardrails via retrieval confidence thresholds.

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JL

Jeffrey Lin

Screened

Mid-Level Software Engineer specializing in Cloud Platform & Automation

Chicago, IL4y exp
RappUniversity of Michigan

Software engineer at Wrap who built production AWS Lambda services for large-scale Parquet dataset generation (50k+ records) and a synthetic traffic/lead generation system using Python, Playwright, and Jenkins. Also built and deployed a full-stack hobby product (MyAnimeListRanker) that ingests MyAnimeList user data and uses an Elo-based ranking workflow, with operational guardrails like rate limiting and monitoring via Vercel/logs.

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SN

Sangwoo Nam

Screened

Engineering Leader and Former CTO specializing in scalable cloud platforms

5y exp
Saidi HealthUC San Diego

Entrepreneurial builder using Claude Code to rapidly prototype multiple product ideas and validate them with target users via social channels. Created and launched NotePulse (a lower-priced Notionlytics alternative), acquiring a dozen early users through Reddit-driven discovery and light paid experiments, with a strong emphasis on MVP scoping and product polish.

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XX

Xinle Xu

Screened

Junior Product Manager specializing in GenAI and global e-commerce

Remote6y exp
ByteDanceNortheastern University

字节跳动实习期间将内部AI重量预测模型从“可用但难上线”的单点能力,改造成可商业化复用的通用API:统一多地区接口与评估口径,设计分层兜底与置信度分级,先灰度上线SEA/JP并推动US/EU落地,结合线上结果进行模型微调。具备LLM/RAG/Agent系统的实战排障方法论,以及面向开发者与售前场景的技术演示与跨团队推进能力。

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CM

Chris Marcus

Screened

Executive CTO & AI Architect specializing in regulated SaaS (InsurTech/Healthcare/FinTech)

Remote15y exp
agentCanvas.aiUniversity of Texas at Austin

Insurance-tech CTO and repeat founder with 10+ years in insurance startups; was employee #4/CTO at Polly (formerly DealerPolicy) and helped scale it from a PowerPoint to 250 employees while raising $180M+. Currently building and selling AgentCanvas.ai—an extensible AI accelerator platform for large insurance agencies—after coding the product end-to-end and now running demos/POCs with prospective buyers.

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NP

Navya Panyala

Screened

Senior Software Engineer specializing in identity, cloud-native microservices, and reactive web apps

Bentonville, AR6y exp
WalmartUniversity at Albany

Product-focused full-stack engineer with Walmart and Dell experience who built and shipped a real-time engagement dashboard end-to-end (Kafka Streams, Spring Boot, React/TypeScript/D3) used daily by business teams, moving them from next-day reports to real-time decisioning. Strong in performance/reliability (Redis caching cut latency ~40%, 90%+ test coverage, Prometheus/CloudWatch monitoring) and production operations on AWS/EKS including handling a cascading failure from a memory leak with zero-downtime rollback and redeploy.

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BG

Engineering Director specializing in distributed systems and enterprise cloud platforms

Waltham, MA10y exp
Dassault SystèmesBoston University

Engineering lead/player-coach working on project management software, owning a high-impact scheduling algorithm rewrite focused on performance, maintainability, and documentation after prior team turnover caused regressions. Previously at EOX Vantage, helped an insurance client modernize monolithic workflows by scoping ambiguous requirements into a roadmap and shipping a day-one MVP before iterating with value-add features.

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CS

Junior AI/ML Engineer specializing in real-time computer vision and tracking systems

2y exp
Credence Management SolutionsUniversity of Maryland, College Park

Full-stack engineer who built and owned a production real-time computer-vision inference platform at Credence, spanning Next.js App Router/TypeScript frontend with SSE/WebSocket streaming, a Flask backend, and Postgres analytics. Demonstrated measurable performance wins (70% fewer re-renders; latency cut to ~40–50ms) and strong production rigor (durable orchestration, idempotency, observability, AWS EC2 + CI/CD) with tight post-launch UX iteration based on analyst feedback.

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CY

Chenfei Yu

Screened

Junior Frontend Software Engineer specializing in React/Next.js micro-frontends

Sunnyvale, CA1y exp
WalmartBoston University

Frontend-leaning full-stack engineer who shipped a civic-tech Next.js/TypeScript app (Boston Police Index) with SSR, dynamic routing, and server-side data fetching, then iterated post-launch with UX and performance improvements. At Walmart (Seller Center micro-frontends), drove large-scale React/TypeScript refactors—standardizing state management, improving hook usage, and cutting type errors ~50%—and earned trust to serve as a code reviewer enforcing quality standards.

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