Vetted Amazon S3 Professionals

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.”

Muhammad Usman

Screened

Mid-level Full-Stack Engineer specializing in SaaS, AI, and Healthcare IT

Gulberg, Pakistan6y exp

“Fullstack engineer with roughly 3 years of experience who has independently built customer-facing systems in healthcare, including invoice notification infrastructure, nurse speech-to-text documentation, and a voice agent/chatbot workflow. Particularly interesting for teams needing hands-on builders who can ship end-to-end products with reliability features, real-time communication flows, and direct user-informed design.”

“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.”

Thimone Noupa

Screened

Mid-level DevOps Engineer specializing in AWS, Kubernetes, and CI/CD automation

Dallas, TX7y exp

“DevOps/cloud infrastructure engineer focused on AWS automation: built GitHub Actions/Jenkins pipelines for containerized deployments with strong security controls and rollback, and implemented Terraform-based AWS provisioning with modular code and remote state/locking. Has led on-prem to AWS migration cutovers with structured risk/rollback planning and stabilization, but has not worked directly with IBM Power/AIX/LPARs or PowerHA/HACMP.”