Vetted Generative AI Professionals

“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).”

Alishba Ali

Screened ReferencesStrong rec.

Senior Full-Stack Software Developer specializing in React/Node and cloud-native apps

GTA, Canada7y exp

“Frontend engineer who launched Emoot (app.emoot.io) end-to-end and recently shipped the "My Savings Goal" feature from UI through production. Emphasizes scalable React + TypeScript architecture (Storybook-driven component library, strict typing, performance profiling/memoization) and pragmatic delivery in tight timelines by reusing existing components/logic and iterating screen-by-screen.”

Billy Kipkorir Bett

Screened ReferencesStrong rec.

Mid-Level Full-Stack Software Engineer specializing in Web3 and AI-enabled SaaS

Remote4y exp

“Frontend engineer who has led end-to-end builds across both Web3 gaming (Next.js app deployed on Telegram) and a sensitive, data-heavy mental health NGO dashboard. Experienced implementing scalable frontend architecture and strict code-quality workflows, plus shipping complex NFT/blockchain pipelines (AI generation → contract deployment → wallet/payment flows) validated on testnets with staged rollout and monitoring.”

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.”

“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.”

“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.”

“Software engineer actively using AI-first development workflows, including Cursor, prompt engineering, and multi-agent setups, to dramatically compress development time. Most notably, they say they built a Regression Optimizer product end-to-end from scratch and used multi-agent approaches to improve troubleshooting and response quality.”

“Built and deployed an LLM-powered automation pipeline that ingests voice and documents, transcribes/extracts key information into structured data, and routes it through backend workflows using Python/FastAPI. Uses n8n to orchestrate multi-step AI processes with validation, retries, and monitoring, and iterates with stakeholders via rapid demos to refine changing requirements.”

Sarang Pratham

Screened

Junior Software Engineer specializing in data engineering and GenAI

Kundapur, India3y exp

“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.”