Vetted System Design Professionals

“Full-stack product engineer who has shipped AI-powered job board moderation and validation features end to end across React/TypeScript, serverless backends, and Postgres. Stands out for combining UX polish, LLM-backed workflow design, and reusable async infrastructure patterns to improve reliability, speed of delivery, and user participation.”

Uvesh Chauhan

Screened ReferencesStrong rec.

Mid-level Full-Stack Developer specializing in AI-powered web and mobile applications

New Delhi, India6y exp

“Builder of multiple AI products including Nova-Core, a multi-model assistant using Grok and Gemini, and Lumina Shield, a prototype for vulnerability detection and performance analysis that routes findings into Nova-Core for explanation and fixes. Also created a desktop voice agent ('Soul') and brings 6 years of experience in a non-profit audio consultancy, with a personal story of being a cancer survivor motivated by purpose-driven work.”

“Casual mobile game designer (Unity-focused) with a psychology background who uses player research and BI analytics to drive retention and revenue. Led major difficulty rebalancing across thousands of levels (reported +5–10% retention lift) and partnered with engineering/art to create a parameter-driven level generation pipeline that quadrupled chapter output and increased release cadence.”

Kumar Chaitanya

Screened

Senior Unreal Engine Game Engineer specializing in real-time multiplayer gameplay systems

Remote, USA6y exp

“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).”

“Early-career backend developer building an Arc Raiders game-data API end-to-end in Go on AWS with PostgreSQL, making their first real deployment and learning system design hands-on. Also built an AI resume and cover letter generator using Gemini and has experience debugging open-source code and managing PRs in a capstone team project.”

“Frontend engineer with freelance and Techtank Toronto experience leading React + TypeScript products end-to-end (UX through implementation). Emphasizes scalable component architecture, accessibility, and performance, and has a pragmatic approach to state management (Redux/Context + React Query) and fast-paced shipping with feature flags and staged rollouts.”

Jithin Mathew

Screened

Mid-level Robotics & Embedded Systems Research Engineer specializing in edge AI for precision agriculture

Fargo, ND5y exp

“Robotics lead engineer (PhD/agriculture research context) who built and iterated a three-unit, wirelessly coordinated greenhouse data-collection robot—solving real-world alignment and comms reliability issues by redesigning the rail/gear system and moving from RF to ESP Wi-Fi with MAC-addressed control. Strong embedded C/C++ background with full-stack robot control implemented from scratch; beginning exposure to ROS 2 via an upcoming field deployment.”

Jayesh Dongre

Screened

Mid-level XR Developer specializing in Unity/Unreal real-time 3D and streaming systems

Pune, Maharashtra4y exp

“Unity VR developer with ~4 years of experience who has shipped an app to the Meta Quest Store. Notably worked on a challenging VR project integrating live point cloud data, focusing on bandwidth/latency, optimization, and compression to keep performance smooth in-headset.”

Muhammad Midhat

Screened

Senior Full-Stack/Backend Engineer specializing in APIs, distributed systems, and AI integrations

9y exp

“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).”