Vetted MongoDB Professionals

“Senior frontend engineer who led the end-to-end build of ConvoCore’s AI agent stress-testing UI, handling non-deterministic AI outputs and high-frequency streaming logs. Emphasizes quality and scalability through schema-driven module contracts (Zod), shared hook/component libraries, and Playwright E2E tests, plus performance work like virtualization and code-splitting. Ships quickly with feature-flag rollouts, Sentry monitoring, and tight user-feedback loops (contextual bug reports with attached logs).”

“Built and productionized a MediCloud/Medicoud LLM microservice platform that lets clinicians query medical data in natural language, orchestrating multi-step RAG-style workflows with LangChain and evaluating/debugging with LangSmith. Delivered measurable gains (consistency ~70%→90% / +20%; latency ~2.0s→1.1s / -40%) by implementing structured prompts, fallback logic across multiple LLMs, hybrid retrieval tuning, and AWS Lambda performance optimizations (package size, async, caching).”

“Frontend/full-stack engineer who has built and scaled multiple national/government platforms in Ethiopia, including an unemployment registration system and a national ID (Fayda) admin/billing dashboard handling contracts, tariffs, inventory, and high-concurrency billing workflows. Strong in React/TypeScript architecture (atomic design, Context/hooks, strict typing) and in integrating identity verification/biometrics-driven business logic with phased rollouts and audit-driven iteration.”

Abdul Rehman

Screened ReferencesStrong rec.

Junior React Developer specializing in full-stack JavaScript web apps

3y exp

“Frontend React developer who helped build a LinkedIn-like social platform (“Fusion Social”), emphasizing scalable project structure (pages/routes vs reusable components) and QA-driven delivery. Uses React Query + Redux Toolkit for API/state management and implements responsive UI based on Figma specs using media queries or MUI breakpoints.”

Umair Shamoon

Screened

Mid-level Full-Stack Developer specializing in MERN/MEAN and cloud-native web apps

8y exp

“Frontend engineer with end-to-end ownership of React/Next.js products, focused on scalable component-based architecture and quality via CI/CD, automated testing, and disciplined PR reviews. Built React + TypeScript dashboards with role-based views using Zustand, and improved existing codebases by decoupling components and boosting performance through code splitting, lazy loading, and standardized shared components.”

Gabe Hoing

Screened

Intern-level software engineer specializing in full-stack and data systems

Spokane, WA2y exp

“Built an AI agent management system in a senior design project to support cybersecurity analysts with gathering and triaging emerging threat intelligence from sources like CISA. Stands out for a thoughtful, production-minded approach to AI development, using specialized agents, strict output schemas, and deterministic controls to manage failure cases.”

“Full-stack AI engineer who has built and deployed multiple end-to-end LLM products, including an AI interview assistant, a multi-agent market research platform, and a policy document explainer. Particularly strong in productionizing agentic workflows, integrating tools like Whisper, Tavus, LiveKit, CrewAI, and LangGraph, and hardening messy real-world AI/document pipelines with validation, memory isolation, and fallback handling.”

“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.”

“Built and shipped a production "Campaign AI" multi-agent system (LangGraph) that personalizes B2B outbound emails at scale using Apollo.io prospect data, clustering-based segmentation, and 21 persona variants. Notably uncovered that high click rates were largely email security scanners and created a validated bot-detection/scoring pipeline (timestamps/IP/user-agent/click patterns), bringing reported engagement down from ~40% to a trusted 5–8% that aligned with real conversions.”

“Data/AI practitioner who built a production LLM-driven healthcare claims analytics and dashboarding system to reduce avoidable ER visits—processing 1.4M+ claims, flagging 19% as non-emergent, and projecting ~$2.8M in annual savings. Demonstrates strong real-world LLM reliability and performance engineering (grounding, numeric validation, caching, materialized views, quantization) plus orchestration experience with Airflow and Azure Data Factory.”

Harshit Vashisth

Screened

Junior AI Engineer specializing in LLMs, RAG systems, and MLOps

Remote, United States1y exp

“Robotics software engineer who built an end-to-end system ("justmatrix"), focusing on multi-agent orchestration and a multi-RAG retrieval backend/API. Has hands-on ROS experience, including a custom node for reliable high-frequency sensor data routing, plus deployment automation using Docker, Kubernetes, and CI/CD.”