Vetted Software Engineers

“Unreal Engine generalist (7 years) with hands-on ownership of end-to-end gameplay systems in real-time 3D C++ and UE5, spanning technical level design, animation/locomotion features, and multiplayer replication. Worked on a shipped Steam title ("Peak 53") implementing replicated systems like prone, scope, and ladder, and has also built MMORPG time/weather systems and a projectile/rocket launcher feature for a demo (Meta Island).”

“Project lead who restored a 1999 vintage museum robotics exhibit by inventorying and integrating legacy systems, reverse engineering original behavior, and reimplementing it in a modern codebase. Notably optimized Tesseract OCR and machine-vision pipelines to run on a 400MHz Pentium III with 256MB RAM while bringing up and tuning degraded FireWire IIDC cameras using scarce legacy documentation.”

“Unity gameplay developer who implemented a zone-based variable-gravity system for a car/racing game ("Electric Car"), requiring careful physics tuning to keep the vehicle controllable and on-screen. Iterates via repeated playtesting to balance feel and smoothness, and uses AI tools to accelerate debugging and unit test work.”

“Built and deployed a production bilingual (Bengali/English) AI virtual assistant that replaced IVR for telecom customer service at massive scale (~15M users), integrating ASR/TTS, Rasa dialogue management, and custom NLP. Overcame low-resource Bengali data and noisy call-center audio with synthetic data augmentation and transformer fine-tuning, achieving significant production gains including ~50% reduction in support calls.”

“Software engineer with hands-on hardware/software crossover work: led an EMG circuit project using PSpice simulation and MATLAB-based data processing. Also contributed to an agriculture research computer-vision effort (hens/eggs tracking), building a PyTorch inference program and boosting model accuracy by ~10–20%, plus limited ROS 2 Humble exposure on an autonomous EV model with LiDAR/camera detection.”

“Frontend engineer who led end-to-end delivery of an HR Service Desk (HRSD) module used daily by HR teams, setting a modular React architecture with standardized data access and shared component libraries. Focused on scaling and performance (lazy loading, memoization, pagination, normalized state) and enforced quality via unit testing, strict code reviews, ESLint, and TypeScript.”

“Frontend-focused engineer and former frontend team lead who built a React product from zero-to-MVP (including complex UI like tables and chat) and implemented scalable architecture, shared typing, and UI quality workflows (Storybook/Chromatic). Also built a React+TypeScript internal dashboard for sales/marketing with filtering/search, and has experience collaborating with designers in Figma while iterating quickly in a startup environment.”

“Early engineering hire at The Coaching Market (B2B2C e-learning startup) who owned re-engineering core REST APIs (FastAPI) and shipping an enhanced Next.js UI, plus automating most deployments via CircleCI/Vercel. Strong in data-driven iteration (surveys/Jira/Slack + Google Analytics, A/B tests) and reliability/performance improvements with measurable impact (30% less downtime, 40% faster releases, 25% faster loads).”

“Sole software engineer for an ecommerce operation who ships and operates full-stack products end-to-end. Built a production AI voice agent integrated with Shopify and internal systems that now handles 4,000+ customer calls/month, plus a branded mobile app credited with $4M+ in sales and a self-serve returns/warehouse platform with strong React/TS UX and robust AWS operations.”

“AI/backend engineer who has built and scaled production LLM-powered SaaS features (document assistant + compliance review agent) on a Node.js/TypeScript + Postgres/Redis stack deployed to GCP Kubernetes. Demonstrates strong production reliability chops—async queueing, autoscaling, observability, and database tuning—with quantified wins (p95 latency -60%, query 4s to <200ms) and robust AI guardrails (strict RAG, schema validation, citations, HITL).”

“Frontend engineer who led an employee management system end-to-end, focusing on scalable architecture and performance (caching, route/component-level code splitting, lazy loading, dynamic imports). Experienced building React + TypeScript dashboards with Tailwind CSS and Zustand, including centralized global UI state for modals/sidebars/preferences and feature-flagged rollouts with rapid QA/iteration.”

“Full-stack engineer who built a lost-and-found pet management platform (React + Node/Express + SQL) with a focus on scalability (stateless JWT auth, modular REST APIs, cloud-based image handling) and performance (Artillery load testing, Chrome DevTools, query/index tuning). Also demonstrates systems-thinking around low-latency real-time voice pipelines integrating WebSockets, ASR, LLMs, and audio output, and has experience translating founder input into shippable product via rapid prototyping.”

“Built and deployed a production LLM-powered recruitment chatbot that automates key recruiting steps (sourcing, candidate engagement, screening). Strong in agent orchestration with LangGraph, including guided graph-based workflows, context-aware routing, and reliability measures like clarifying steps plus human-in-the-loop evaluation.”

“Full-stack engineer working on a medical practice SaaS, who owned an end-to-end charge entry module handling patient charges/payment workflows and complex client-side data transformations. Also built a fintech rating platform with real-time WebSocket streaming and TradingView-based charting, and has 10 years of university experience mentoring student "startup" capstone projects under tight deadlines.”

“Backend ERP developer specializing in Odoo (Python MVC) with hands-on experience integrating ERP workflows with external SQL databases and handling cloud deployment compatibility issues. Led a migration of ~40 years of legacy data into a modern ERP using scripted transforms and unique identifiers to preserve data integrity, and has experience implementing role-based permissions and preventing failure modes in SQL status update flows.”

“AI/ML practitioner with production experience building a RAG-powered contextual customer support agent, optimizing for low latency using vector databases and smaller LLMs. Also deployed a fraud detection model on Kubernetes with auto-scaling for heavy transactional loads, and improved chatbot accuracy by 15% through metric-driven testing and evaluation. Partners with Marketing on personalization/recommendation initiatives with measurable outcomes tied to customer feedback.”