Vetted JavaScript Professionals

“Built and deployed a production LLM-powered document Q&A system using a strict RAG pipeline (LangChain-style orchestration + FAISS) to help users query large internal document sets. Demonstrates strong reliability focus through hallucination mitigation, curated offline evaluation with grounding checks, and production monitoring (latency/fallback rates) plus stakeholder alignment via demos and business metrics.”

“Unity/VR gameplay engineer who has shipped full games and built a robust coin economy + massive gear customization system (over a million combinations) backed by a cloud service. Notably discovered and fixed a severe backend security flaw by adding proper authentication (security key + OAuth2), and has hands-on VR performance optimization experience (OVR Metrics, LOD/mipmaps, imposters) plus multiplayer sports sync design using Photon PUN2.”

“Backend engineer who built and evolved Python/FastAPI services (including AWS-deployed ML prediction APIs) for real-time profitability and risk insights at TenXengage. Emphasizes pragmatic architecture, strong validation/observability, and secure access controls (RBAC + row-level filtering), and has led safe migrations via parallel runs and incremental rollouts; reports ~20% forecasting accuracy improvement.”

“Built and deployed an LLM-powered clinical decision support and risk monitoring platform for mental health at Valuai.io, emphasizing low-latency, evidence-grounded responses and crisis-safe behavior with clinician escalation. Strong production agent-orchestration background (LangChain/CrewAI) plus rigorous evaluation (clinician-in-the-loop + evaluator agent) and large-scale synthetic testing; also applied multi-agent workflows to document verification and fraud detection during an AI internship at Nixacom.”

“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.”

“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.”

“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.”

“Unity gameplay/game-flow programmer with ~10 years in the games industry who has shipped on Meta Quest 1 & 2. Built a Steam-available multiplayer "Vampire Survivors"-style co-op demo largely solo in a 6-month contract, handling everything from networking and UI to performance optimization (GPU instancing) and Steam publishing.”

“IT Analyst/research background with hands-on experience deploying and hardening a multi-agent AI support/triage system (ticket ingestion + knowledge-base retrieval) with strong emphasis on reliability and observability. Has debugged real production issues spanning backend services and network latency (sync failures/partial writes) and is comfortable in Linux environments; also has academic exposure to robotics simulation and ROS2.”

“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.”

“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.”

“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.”

“Frontend engineer who led end-to-end delivery of a Next.js/TypeScript product, including a permission-based React dashboard for managing employee gift card bonuses across large companies. Demonstrated strong architecture and quality practices (multi-reviewer PR workflow), plus performance-focused UX for bulk Excel uploads using Ant Design forms with inline validation and efficient row updates. Known for close product/design collaboration to simplify complex workflows into step-based, user-friendly flows and for shipping quickly with tight QA/Jira-driven iteration.”

“Frontend engineer who has led end-to-end builds (including an SSR Vue 3 app) and delivered complex React + TypeScript internal dashboards for a fintech (Sycamore). Demonstrated strong architecture and performance chops, including refactoring a large internal tool with lazy loading and route-based code splitting to improve load speed by 64%, and operating within a robust CI/CD + QA pipeline.”

“Unity VR/AR developer with 10 years of experience who built a complex multiplayer online Jenga game from scratch, including VOIP and a custom physics synchronization approach to make heavy physics work smoothly online. Has also delivered VR simulation experiences for an educational institution using drone-recorded 360 video placed into a virtual cockpit flight experience (deployed directly to Quest headsets, though not launched on the Quest store).”

“Unity developer who has shipped VR games on Meta Quest/Oculus Go and demonstrates strong performance engineering for constrained hardware (multithreading, Unity Job System, Jump Point Search). Has built multiple games largely solo (e.g., Tap & Conquer), handling UI/flow, core gameplay, and save systems, and uses AI to speed up build/test/backup automation via shell scripting.”

“Senior Unity Developer / Tech Lead who has shipped Unity games across a wide range of platforms (mobile, stores, WebGL, Steam). Built two full Unity game frameworks solo—a slots engine used for 100+ games and a bingo engine used for 9+ games—owning architecture, core gameplay systems, UI, performance optimization, and SDK integrations.”

“Frontend lead with ~6 years building edtech platforms (LMS + CMS) using Svelte and React/TypeScript. Manages a 6–7 person team and owns architecture, CI/CD, and production quality practices (error boundaries, crash/downtime alerting). Has hands-on experience improving performance at scale via micro-frontends, lazy loading/code splitting, and virtualization/pagination for heavy UI screens (e.g., Bonzo game platform).”

“Frontend engineer who led the Dash Merchant App and Backoffice platform (React/TypeScript/Redux) supporting $50M+ in monthly transactions. Focused on scalable architecture and reliability—introduced typed API layers, centralized error handling, and performance optimizations (including ~40% load-time reduction) while driving team adoption through incremental refactors, templates, and pairing.”

“Robotics software engineer with hands-on hardware integration who built an AI-enabled smart dog door using a Raspberry Pi, camera-based recognition (DeepFace adapted for dogs), and stepper motor control (TB6600/NEMA 17). Experienced in ROS/ROS 2 across perception-to-controls, rigorous bag-driven debugging of SLAM/navigation issues, and deploying robot software with simulation-in-the-loop testing plus Docker/Kubernetes CI/CD.”