Vetted Authentication Professionals

ATIF FATTANI

Screened ReferencesStrong rec.

Mid-level Full-Stack Developer specializing in MERN, mobile apps, and business automation

Karachi, Pakistan5y exp

“Full-stack builder who appears to have owned Qualifychat end-to-end as a solo contributor, spanning React/TypeScript frontend, backend APIs, AI-driven lead qualification, scoring, and admin dashboards. Strong focus on turning complex automation into simple business workflows, with additional experience building tools like Write Guard and an HR CRM.”

“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.”

“Backend engineer focused on reliability and production operations, with hands-on experience implementing an outbox pattern to keep database updates and downstream events consistent. They also described diagnosing transaction-related latency under heavy client traffic and using monitoring data to validate performance improvements, showing a pragmatic, systems-oriented approach to scaling integrations.”

Ridwan Oladipupo

Screened ReferencesStrong rec.

Senior Frontend Engineer specializing in React, Node.js, and AWS

Halifax, Canada11y exp

“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.”

“Built and shipped a production Python-based agentic RAG document retrieval system over 80K records using FastAPI, OCR, vector search, and AWS infrastructure, with a strong emphasis on reliability, testing, and observability. Stands out for treating AI failures like production incidents—turning hallucinations, retrieval misses, and OCR issues into regression tests—and for quantifiably reducing document lookup time from about 12 minutes to under 90 seconds.”

Ronald Forte

Screened ReferencesModerate rec.

Entry-Level Software Engineer specializing in AI APIs and RAG systems

0y exp

“Junior/entry-level AI/LLM engineer who built a production-oriented RAG onboarding and knowledge assistant that ingests GitHub repos and internal sources (e.g., Confluence/Jira) using ChromaDB, with reliability features like retrieval fallbacks, retries, caching, and monitoring. Currently implementing a LangGraph-based multi-agent workflow with intent routing and Pydantic/Magentic-validated structured outputs, plus CI/CD offline evals and online metrics (Grafana/Prometheus) to improve predictability and reliability.”

“Unity/VR engineer with nearly 15 years of experience, specializing in multiplayer architecture, cross-platform systems, and developer tooling. He built and shipped a reusable Unity Netcode-based multiplayer stack with authentication, matchmaking, Vivox voice chat, and custom host migration that reportedly improved development speed by 70% to 80%, and has also supported releases across Meta Quest, consoles, and mobile-related ecosystems.”

Priyank Jhaveri

Screened ReferencesModerate rec.

Junior AI/ML & Mobile Engineer specializing in LLMs, synthetic data, and React Native

New York, United States1y exp

“Currently at Uplift AI shipping production LLM features that generate personalized growth insights from user reflections using BERT + embeddings + RAG, with strong safety/guardrail practices for sensitive contexts. Also built an end-to-end React Native UGC challenge submission/moderation system that improved repeat submissions and 7-day retention, and has applied rigorous clinical-style evaluation methods on a dental X-ray disease detection project to reduce false negatives.”

“Built and owned an end-to-end Python/Postgres job-tracker backend that scrapes job postings (including LinkedIn) using Selenium-driven real-browser automation, with deduplication and data-quality filtering. Has practical experience migrating deployments from DigitalOcean to Vercel and emphasizes documentation, roadmapping, and testing as part of an iterative delivery cycle.”