Vetted Prompt Engineering 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).”

“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.”

Abhay Bisht

Screened

Junior Software Engineer specializing in AI-powered full-stack SaaS

Bangalore, India2y exp

“AI-first developer who reports using agents for roughly 85% of coding work, with a disciplined process centered on detailed specs, prompt design, review, and testing. Has built a personal multi-agent orchestration setup with specialized agents for testing, PR extraction, review, and synthesis, and stays current through AI engineering newsletters and a network of AI companies.”

“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.”

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.”

Jaiden Kettleson

Screened ReferencesStrong rec.

Entry-Level Full-Stack & AI Engineer specializing in chatbots and web apps

1y exp

“Data Science honors graduate (Maryville University) who has built Python/SQL backends and a capstone website handling sensitive user data. Emphasizes secure data handling (password encryption, secure database updates) and uses Git/GitHub Pages with CI/CD-style practices for managing and deploying changes.”

Uvesh Chauhan

Screened ReferencesStrong rec.

Mid-level Full-Stack Developer specializing in AI and cybersecurity platforms

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.”

“Educator-turned-product builder who has led end-to-end onboarding and training platform builds for nonprofits and universities, often as a solo operator handling discovery through implementation. Brings a distinctive blend of instructional design, UX simplification, and human-centered AI thinking shaped by hands-on teaching and tutoring experience.”

Mahad Asif

Screened ReferencesModerate rec.

Mid-level Game Developer specializing in Unity, AR/VR, and cross-platform products

Rawalpindi, Pakistan4y exp

“Exceptionally young game developer who says he began at age 10 and was employed as a Unity developer at 13. He has hands-on experience building gameplay systems, VR/Web/mobile projects, Photon multiplayer features, and AI/ML experiments—including an open-source protein-model research pipeline reportedly under peer review at PLOS ONE.”

Muhammad Murtaza Murtaza

Screened

Mid-level Machine Learning Engineer specializing in NLP, Computer Vision & Predictive Analytics

Islamabad, Pakistan5y exp

“Built a production LLM fine-tuning pipeline for domain-specific code generation at Pigeonbyte Technologies, including automated collection and rigorous quality filtering of 10M+ code samples (AST validation, sandbox execution/testing, deduplication, drift monitoring, and human-in-the-loop review). Also implemented end-to-end ML orchestration in Apache Airflow with data quality gates, dataset versioning in S3, benchmarking, and automated model promotion, and has a reliability-first approach to agent/workflow design.”

“Unity/C# gameplay engineer based in Portugal who shipped an AI-driven NPC narrative/quest system for a live mobile RPG, integrating Google Gemini via function-calling with strict JSON schemas to keep a deterministic game loop safe from hallucinations. Emphasizes high-performance engineering (zero per-frame GC, locked 60 FPS) with rigorous PR reviews and profiling gates, plus robust async/network patterns (UniTask, CancellationTokens) and LLM cost control via sliding-window context management. Seeking independent B2B contractor work at $45k–$50k USD/year.”

“Built production-style backend and AI systems across internship and project work, including a real-time sports platform backend and a Smart Email Assistant using GPT-4. Stands out for combining classic backend performance engineering with practical LLM workflow design, including measurable latency improvements, high uptime, and debugging of non-deterministic model behavior.”

Tejaswi devarapalli

Screened

Junior Software Engineer specializing in backend systems and AI infrastructure

Los Angeles, CA2y exp

“Built both a full-stack AWS file-processing pipeline and a production AI document Q&A system ('smart-doc'). Stands out for combining strong cloud engineering with practical LLM/RAG architecture, including hybrid retrieval, reranking, structured outputs, confidence-based retries, and production monitoring.”

“Fullstack engineer with a strong serverless/AWS and applied AI profile, having built document-upload-to-RAG chatbot systems using Bedrock/Titan as well as a production fintech reporting platform. Particularly compelling for teams needing a zero-to-one builder who can own architecture, frontend, backend, and user-informed product delivery; one recent product reached 100+ student users within 48 hours of launch.”

Ethan Martin

Screened

Senior Unity Developer specializing in desktop and XR simulation apps

Remote4y exp

“Unity/C# developer who built and continues to evolve a data-driven product configuration system for complex medical equipment—reverse-engineering undocumented, massive databases and generating 3D configured products with extensive rules—helping users (e.g., hospital sales workflows) save time and support increased sales. Also built an internal LLM-powered debugging assistant using structured Unity/backend telemetry and has hands-on Unity Netcode experience in smaller multiplayer prototypes.”