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Vetted JavaScript Professionals

Pre-screened and vetted.

KS

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

Middletown, DE2y exp
VibeSea AIUSC

Distributed-systems engineer applying robotics-style patterns to software: built "Vibecheck," a high-throughput real-time video + OS-telemetry fusion and analysis system (500+ MB/session) with strict latency constraints. Strong in containerization and CI/CD (Docker, GitHub Actions) and in designing fault-tolerant, event-driven architectures (Kafka/RabbitMQ), plus hands-on debugging of multi-agent coordination using blackboard + watchdog/circuit-breaker control patterns.

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SC

Shujie Chen

Screened

Entry-Level Full-Stack Software Engineer specializing in web, mobile, and distributed systems

Remote0y exp
Jiangxi Arts & Ceramics Technology InstituteUSC

Backend engineer who built a Logistics-as-a-Service platform in Go, proactively refactoring a monolithic REST service into gRPC microservices to improve performance and maintainability. Led a 3-person team with disciplined code reviews, Dockerized DB migrations, and a canary-style rollout (5% traffic) monitored for latency and failures; also implemented JWT/OAuth2 RBAC and production-minded edge-case handling in an ordering system.

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TP

Mid-level Python & AI/ML Engineer specializing in backend APIs and MLOps

USA6y exp
Capital OneUniversity of Memphis

Built and deployed a production LLM/RAG document automation system for business documents (contracts/claim forms) that extracts schema-validated JSON, generates grounded summaries/Q&A, and integrates into transaction systems via APIs. Emphasizes real-world reliability: hallucination controls, layout-aware parsing with OCR fallback, Step Functions-orchestrated workflows with retries/timeouts, and human-in-the-loop review designed in close partnership with operations and claims stakeholders.

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YP

Yash Pise

Screened

Mid-level Data Scientist specializing in Generative AI, LLMOps, and clinical data pipelines

5y exp
NovartisStevens Institute of Technology

LLM/RAG engineer who has built and deployed corporate-scale systems at Novartis and Johnson & Johnson, including a healthcare AI agent that generates day-to-day treatment schedules. Recently handled a high-stakes safety incident (LLM suggesting overdose) by tightening model instructions and validating with ~200 test prompts, and has strong end-to-end data/embedding/vector DB pipeline experience (PySpark, FAISS, Pinecone) plus SME-in-the-loop evaluation (RLHF).

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MI

Senior Frontend Engineer specializing in React and TypeScript

Kitchener, Canada11y exp
CartaObafemi Awolowo University

Frontend engineer with deep experience modernizing KYC flows at Carta, including rebuilding country-specific KYC forms into a scalable configuration + validation-schema system that cut new-jurisdiction support from 2–3 months to ~2 weeks. Strong on quality and rollout practices (E2E/backend testing, early QA engagement, staged/A-B rollouts) and performance optimization for heavy React/TypeScript dashboards using Intersection Observers for lazy loading.

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EL

Ethan Lam

Screened

Junior Software Engineer specializing in data platforms and full-stack development

Toronto, Ontario3y exp
Warner Music GroupUniversity of Toronto

Software engineer with Warner Music Group experience owning and shipping analyst-facing data products (marketing/streaming data dashboards) end-to-end with high adoption through continuous stakeholder feedback. Also builds side projects with TypeScript/React and domain-driven API design, emphasizing flexibility (including swapping databases mid-development) and pragmatic microservices reliability patterns (logging, timeouts, retry backoff).

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TT

Thomas To

Screened

Mid-level Full-Stack Engineer specializing in AI/ML data platforms for biotech and FinTech

Emeryville, CA6y exp
Canventa Life SciencesUC Davis

AI/ML full-stack practitioner in a small-scale manufacturing/lab operations environment who deployed a production ML system to improve blood cell order fulfillment by predicting yield/success from donor characteristics. Experienced building custom multi-agent orchestration (Python, LangChain/LangGraph, MCP) and balancing reliability, data quality constraints, and token/ROI economics while communicating tradeoffs to VP-level business stakeholders.

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PP

Junior Full-Stack Developer specializing in microservices and scalable web apps

Oakville, Canada2y exp
EnergywellUniversity of Toronto

Full-stack developer (Energywell) who led an internal admin dashboard end-to-end using React/Redux and a Go microservice, emphasizing performance (reduced calls, preload data) and maintainable architecture (modularity, refactoring, PR reviews). Also shipped a Redis-based caching whitelist feature in a fast-paced environment and helped implement a responsive, brand-configurable onboarding/signup frontend.

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LS

Mid-level Software Engineer specializing in cloud-native microservices and workflow automation

TX, USA5y exp
ServiceNowCalifornia State University, Long Beach

Enterprise platform engineer/product owner who led end-to-end delivery of customer-facing ServiceNow Service Catalog/workflow solutions, emphasizing reliability, security, and fast iteration. Built React/TypeScript portals with Node.js and Spring Boot backends, and improved microservices reliability at scale using Kafka, monitoring, and robust retry/timeout patterns.

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SA

Mid-level Software Engineer specializing in AI agents, backend systems, and data engineering

4y exp
AmazonGeorgia State University

Amazon engineer who built a production AI agent platform (Python/AWS Strands on Bedrock) that lets teams create tool-using, multi-agent workflows—e.g., agents that auto-triage and resolve customer support tickets by reading internal documentation and collaborating with a research agent. Previously worked in Deloitte on IAM using Ping Identity/Ping DaVinci orchestration, and applies orchestration thinking plus structured evaluation (LLM-as-judge, surveys, automated tests) to improve agent reliability.

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VR

Engineering Manager specializing in payments orchestration and checkout platforms

Toronto, Canada12y exp
ChargebeeVellore Institute of Technology

Frontend engineer who led end-to-end architecture for a cross-platform Payments Checkout SDK at Inai Technologies, scaling it to support iOS/Android/React Native/Flutter/Capacitor and powering 2.4M+ transactions per month. Emphasizes performance (bundle size/tree-shaking), OTA update delivery for mobile wrappers, and strong engineering guardrails (SonarQube, Snyk, CI/CD, regression suites, Sentry/PostHog) to ship quickly with high quality.

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VR

Vaman Rao

Screened

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

NJ, USA5y exp
UberConcordia University Wisconsin

Backend engineer focused on Python/FastAPI microservices, with hands-on experience deploying to AWS (EKS/ECR) via Jenkins and GitOps-style workflows using ArgoCD. Has built and stabilized real-time Kafka payment-event streaming pipelines and improved production performance under peak load through Redis caching, SQL optimization, and robust retry/DLQ patterns. Also supported phased migrations from on-prem environments to AWS with gradual traffic shifting and monitoring.

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JA

João Arruda

Screened

Senior Frontend Engineer specializing in Vue.js, testing strategy, and scalable architecture

Remote, EU15y exp
TheyDoSENAC São Paulo

Frontend engineer/lead focused on scalable architecture and reusable UI platforms: built a schema-driven, IoC-based unified filtering system across an app with feature-flagged rollout and strong TypeScript/testing discipline. Also created a standalone React NPS survey package that works across microfrontends (handling peer dependency/version issues) and implemented accessibility improvements for complex interactions like drag-and-drop while leading an Atomic Design → Feature-Sliced Design migration.

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SL

Samuel Luther

Screened

Senior Software Engineer specializing in full-stack systems, data pipelines, and ML

Seattle, WA8y exp
ExponentGeorgia Tech

Built and productionized an autonomous research agent (AutoGPT) in a Docker/Kubernetes environment with Pinecone-based long-term memory and custom Python tools for analysis, visualization, and report drafting. Implemented layered guardrails (prompt templates, automated validation, self-critique loops, and monitoring) and achieved ~25% reduction in manual report generation time while scaling the workflow to support multiple concurrent users.

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HG

Hardik Goyal

Screened

Senior Integration Developer specializing in enterprise automation and data integration

United States4y exp
Vail ResortsPurdue University

Frontend-focused engineer with experience building and optimizing React-based dashboards and reusable component libraries in a multi-team, internal open-source-style environment at Merck (ClearSight Forecasting Dashboard). Also handled production user issues on a live streaming platform (GameSee.tv) and built a financial application from scratch at Manipal Business Solutions, owning backend services, middle-tier APIs, and third-party integrations.

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NT

Natalie Tsang

Screened

Intern Mechatronics/Robotics Software Engineer specializing in ADAS and ROS2

Waterloo, ON1y exp
Harbinger MotorsUniversity of Waterloo

Robotics software engineer with experience spanning embedded C++ control on microcontrollers and ROS/ROS2 production systems in automotive and marine robotics contexts (Harbinger Motors, Impossible Metals). Has deep hands-on experience debugging real-time image pipelines (DDS/QoS tuning, HIL stress testing) and building large automated test suites (1200+ tests) plus CI/CD (Dockerized Playwright tests on Jenkins).

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JL

Jungbeom Lee

Screened

Mid-level Mobile Software Engineer specializing in Android performance and growth

Irvine, CA6y exp
FreelanceUCLA

Backend engineer with primary experience in Node.js and serverless AWS/Firebase architectures. At iSharingsoft, owned a data sync protocol optimization effort—used server log analysis to find redundant read/write calls, redesigned sync logic, added caching, and reduced server traffic by 15%, improving performance and cost.

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MS

Mid-level Software Engineer specializing in FinTech full-stack and AI applications

Remote, USA3y exp
JPMorgan ChaseArizona State University

Built and productionized an NLP-powered customer support assistant at JPMorgan Chase for digital banking, focused on reducing response time for repetitive client queries. Strong in real-world AI deployment challenges—sensitive data handling, low-latency FastAPI services, and AWS/Kubernetes operations with CI/CD—plus a metrics- and guardrails-driven approach to reliable AI workflows.

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CM

Mid-level Full-Stack Java Developer specializing in payments and event-driven microservices

Arlington, VA5y exp
IntuitGeorge Washington University

Full-stack engineer (backend-led) with recent experience building enterprise workflow orchestration and billing/payment platforms at Intuit using Java/Spring Boot (WebFlux), Kafka, Postgres/Redis, and React/TypeScript. Has operated at high scale (reported ~1200 RPS during month-end billing) and focuses on event-driven microservices, real-time UI updates via streaming, and disciplined API evolution with contract testing.

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HR

Harsh Ranpura

Screened

Mid-Level Software Engineer specializing in FinTech payments and fraud detection

Remote, USA3y exp
MastercardLoyola Marymount University

Backend/platform engineer with payments domain experience, having owned core services for MasterCard’s global card tokenization and settlement platform. Built Django/Celery microservices plus Kafka/Redis real-time fraud streaming, delivering 27% latency improvement, sub-100ms fraud checks, and 18% fewer false positives. Strong DevOps/IaC background across Kubernetes, AWS ECS, Terraform, GitHub Actions, and GitOps practices for high-scale transaction systems (including UPI at PhonePe).

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NT

Mid-level Software Engineer specializing in cloud-native microservices and data platforms

Downingtown, PA5y exp
Pike SolutionsNYU

Backend engineer with experience at Comcast and in healthcare/pharmacy automation (PrimeRx), building Python/Flask services that orchestrate large-scale batch workflows (Airflow) and high-throughput event processing (Kafka). Demonstrated measurable performance wins (cut provisioning latency to ~150–200ms) and strong multi-tenant isolation strategies (Postgres RLS, partitioning), plus practical integration of ML model outputs into production systems with validation and fallback controls.

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MB

Mahesh Babu

Screened

Mid-level Full-Stack Developer specializing in cloud-native FinTech systems

New York, NY4y exp
Goldman SachsClemson University

Built a lightweight internal JavaScript analytics tracker capturing user interactions (clicks, page views, custom events) with debounced batching, automatic session tracking, and offline event caching via a localStorage-backed append-only queue. Demonstrates practical performance optimization mindset (profiling, memoization/caching) and React performance tuning.

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ZL

Zuocheng Li

Screened

Entry-Level Software Engineer specializing in full-stack web and Android development

San Jose, CA0y exp
San José State UniversityUSC

Early-career developer whose experience comes from classroom projects but has completed full end-to-end web app delivery: implemented login/search/favorites, integrated external APIs, and deployed to Google Cloud for multi-device use. Demonstrates user-centered iteration by recruiting friends to test and provide feedback, and has hands-on production-style debugging experience (e.g., resolving CORS issues during deployment).

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HK

Harini Kv

Screened

Mid-level AI/ML Engineer specializing in GenAI, NLP, and MLOps

Dallas, TX7y exp
EquinixFitchburg State University

GenAI/data engineering practitioner with production experience across Equinix, Optum, and Citibank—built an Azure OpenAI (GPT-4) + LangChain document intelligence platform processing 1.5M+ docs/month and a HIPAA-compliant Airflow healthcare pipeline handling 5M+ claims/day. Also delivered a real-time fraud detection + explainability system using LightGBM and a fine-tuned T5 NLG component, improving fraud accuracy by 15%+ while partnering closely with compliance stakeholders.

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