Vetted TypeScript Professionals

Balaji Vellaluru

Screened ReferencesStrong rec.

Mid-level Software Engineer specializing in full-stack and computer vision systems

Chicago, IL3y exp

“Built D.O.C.T.O.R, a 0-to-1 anatomy learning platform with 450+ 3D models that reached 6,500+ users, saved $850K versus a costly alternative, and was featured in a University of Illinois Chicago news article. The candidate combines product initiative with hands-on full-stack execution, spanning React/Three.js, databases, auth, analytics, and AI workflow automation side projects.”

“AI/back-end engineer at Canon who helped build and operate an internal production LLM platform that acts as a secure middle layer between users and models, defending against jailbreaks/prompt injection while enabling RAG, memory, and grounded responses over company data. Experienced with LangChain/LangGraph orchestration, vector DB retrieval, and reliability practices (testing, monitoring, adversarial prompts) to run high-throughput, low-latency AI workflows in production.”

“Front-end engineer who has independently built sophisticated browser UIs in regulated and high-visibility environments, including an FDA-related medical research dashboard with AI-powered document search and a large-scale animated event site for Prologis. Stands out for combining deep browser performance expertise with strong UX instincts for expert users working with complex, data-heavy workflows.”

“Built and deployed LLM-powered features for a startup organizational management application, focusing on real-world deployment constraints like latency and cost. Implemented RAG with FAISS and improved retrieval quality by switching embedding models (OpenAI/Hugging Face) and fine-tuning embeddings on medical corpora for a medical-report UI feature. Uses LangChain and LangGraph to orchestrate multi-node LLM API workflows and evaluates systems with metrics like latency, cost per request, and error taxonomy.”

Iangolana Riantsoa RAMELSON

Screened ReferencesStrong rec.

Mid-level Full-Stack JavaScript Developer specializing in React, Next.js, and TypeScript

Madagascar, Madagascar5y exp

“Frontend engineer who led end-to-end delivery and scaling of an internal HR product (Easy Time), owning architecture decisions (React/TypeScript, Redux Toolkit, Tailwind/shadcn). Experienced building complex dashboard UIs with advanced filters and real-time interactions, collaborating directly with design (Figma) and shipping quickly via incremental delivery and GitLab CI-driven deployments.”

Tanya Parker

Screened ReferencesStrong rec.

Senior Frontend Developer specializing in WebXR and Three.js

London, UK9y exp

“XR professional with 9 years in the industry and 3 years using Unity; built a solo Unity city-building/resource management game (BLEAK) inspired by Anno in a dystopian cyberpunk setting. Has shipped web-based XR experiences (not Unity headset titles) and emphasizes pragmatic scope control and production adaptability, honed further during time at Zappar.”

Kamran Ali

Screened ReferencesStrong rec.

Senior Frontend Developer specializing in React and Next.js performance & SEO

Tbilisi, Georgia8y exp

“Frontend engineer who led end-to-end builds for chauffeur/service platforms (Mychauffeur.com, comfydrive.com), implementing Atomic Design architecture with Next.js, MUI, and Redux. Experienced in building React+TypeScript dashboards, improving performance via SSR migration, and shipping high-risk features like MADA payment integration with Cypress-based QA and Sentry monitoring.”

Syed Mujtaba

Screened ReferencesStrong rec.

Senior Frontend Developer and MERN Stack specialist

Pakistan9y exp

“Frontend engineer experienced leading client-facing portals (including WebGL integrations) and admin panels, with a strong focus on scalable architecture (monorepo, shared design system/atomic design) and performance. Has built complex React+TypeScript workflows like multi-step user creation with dynamic forms, and ships major features (e.g., video recording) using feature-flagged, trunk-based delivery and E2E testing.”

“ML/NLP practitioner who has delivered production systems in regulated domains, including a healthcare compliance pipeline using RAG (GPT-4/Claude) plus TF-IDF retrieval that increased document review throughput 4.5x. Also has hands-on experience improving fraud detection data quality via entity resolution (Levenshtein, Dedupe.py) validated with A/B testing, and building scalable, monitored workflows with Airflow, CI/CD, and AWS SageMaker.”

“Full-stack developer who uses AI deliberately rather than blindly, keeping generated code to a minority of core feature work so they retain full understanding of data flow. Built a React/TypeScript + Supabase task management app and shows strong judgment around debugging hallucinated schema/query output, refactoring for maintainability, and prioritizing security and logic over boilerplate speed.”