Hire the Best Deltek Vision Specialists
in the United States

Systems Architect & Project Lead | AI-Driven, Privacy-First Platforms Profile Summary I’m a systems architect, project leader, AI workflow specialist and full stack developer with over 20 years of experience helping companies transform ideas into working systems and working systems into traction-worthy platforms. My leadership style blends AI-assisted workflows, remote/international collaboration, and ethical AI development, with a strong focus on privacy-first design, secure architecture, and compliance in regulated domains like healthcare. I’ve worked with founders to refine MVPs, unlock early traction, and build credibility for investor submissions, including Y Combinator. In the healthcare and legal space, I’ve prototype systems that power clinical decision support tools, secure patient messaging, and HIPAA-aware data storage. My work includes evaluating chatbot safety in therapy use cases, rethinking EHR-compatible workflows, and building privacy-first AI infrastructure for medical applications. In the Legal space I've worked on making court filings ethical and accurate when AI is used. I bring clarity and execution to ambiguous ideas — especially in emerging spaces like generative AI, health tech, and secure systems that defy traditional product boundaries. Whether you’re building your first product, scaling a prototype, or laying the foundation for a HIPAA-compliant AI platform, I can lead from concept to delivery. ⸻ Representative Success • Deployed IAM-driven SageMaker Studio ML pipeline in under 1 week, complete with model lifecycle management and enterprise MLOps orchestration • Designed and implemented legal and healthcare chatbot platforms leveraging custom models (e.g., LegalBERT), RAG architecture, and secure vector-based retrieval • Prototyped HIPAA-aligned healthcare messaging systems for reliability, performance, and clinical usability • Led remote international teams in health- and legal-tech domains, managing AI resource allocation, QA cycles, and ethical compliance • Authored a leading-edge AI tech blog and published original research on encoding systems, AI privacy, and regulatory-safe architectures ⸻ Areas of Expertise • AI modeling & generative systems • Architecting scalable, privacy-first platforms • Clinical systems & HIPAA-aware workflows • Secure comms & chatbot risk assessment • Project leadership & team orchestration • MVP strategy & investor narrative support • YC-style engagement and submission readiness • Ethical AI implementation • Mobile platforms (iOS, Android) – 20+ years • Legal tech, health tech, and regulatory systems (HEES, Sub-Lex, etc.)

I'm a U.S.-licensed Journeyman Electrician with 18+ years of field experience and over a decade specializing in Lutron lighting control systems. I've spent the last several years as lead programmer for award winning high-end residential integration firms — so I know exactly what a stuck project looks like from the integrator's side, and how to get it moving again, remotely and fast. I help integrators and homeowners with: Remote troubleshooting — diagnosing and resolving system failures on Lutron HomeWorks QS, RadioRA2/RA3, and Ketra, often while you're still on the jobsite Programming & optimization — custom scene design, astronomical time clock scheduling, and keypad/sensor logic integration Design & code review — evaluating Lutron control system layouts before install to catch problems while they're still cheap to fix If you're an integrator without in-house Lutron programming support, or you're behind schedule on a job, I can usually get on a call same day.

🚀 Applied AI Engineer | LLM Apps, RAG & AI Agents (MCP, LangChain, AutoGen) | Computer Vision | Python, AWS, GCP | Health-Tech & Science - Overview I build and ship production AI systems myself, end to end: agentic workflows, LLM-driven RAG, and computer vision pipelines that make it out of the notebook and into real products. I bring 8+ years of applied ML and deep learning engineering, an M.S. from Carnegie Mellon's School of Computer Science, and a B.S. in Biomedical Engineering from Penn State. My specialty is turning complex scientific, health-tech, and business logic into scalable, production-ready AI. ✅ What I Build: • Agentic AI: Multi-agent workflows, MCP integrations, tool/function calling, and autonomous web agents using LangChain, LangGraph, AutoGen, and OpenAI • LLM Applications: Enterprise chat and RAG systems with agentic context engineering (ACE), systematic evals, tracing, and RAG dashboards • Model Customization: Llama fine-tuning (SFT), LLM-as-a-Judge evaluation pipelines, prompt engineering with monitoring • Computer Vision: YOLO, Vision Transformers, and CNN pipelines for detection, segmentation, and health-metric extraction, deployed with TorchServe, Prometheus, and Grafana • Full-Stack + DevOps: Python, TypeScript, React/Next.js, Django, AWS, GCP, Docker, Kubernetes, Terraform, CI/CD 🎯 Recent Hands-On Builds: • LLM-driven RAG system with agentic contextual reasoning (ACE, from Stanford's Zou Lab) powering enterprise chat services, with tracing, metrics, and eval datasets for pipeline studies • SFT fine-tuning of Llama models on web-navigation data and LLM-as-a-Judge evaluation for MultiOn's autonomous web agent (Chrome extension + API) • Blood-based, organ-specific aging clocks on the NHANES dataset (PyTorch, Spark, Cox survival modeling), plus internal agentic workflows (Khoj, Danswer) for function calling and GitOps • Co-founded EzOut and built the end-to-end YOLOv7 retail vision pipeline: data labeling, training, and TorchServe deployment with Prometheus/Grafana monitoring, plus the Django/React customer service • Production CV for eye tracking and health-metric extraction: multi-class segmentation, multi-task regression, and semi-supervised labeling workflows with SVM-based data QA • 1st place, AGI House MCP Build Day: deployed an MCP-powered brand-SEO analytics agent to Fetch.ai's Agentverse and ASI:One 🔬 Why Science and Health-Tech Teams Hire Me: I started in the lab, not just the IDE: spatial biology, NGS, PCR, and GLP lab automation at Rebus Biosystems and Prenetics, a co-authored spatial transcriptomics conference paper, and digital pathology research at CMU benchmarking Vision Transformers against CNN ensembles. I speak both scientist and engineer, so your domain experts never have to translate for me. 🔧 Technical Stack: AI/ML: OpenAI (GPT), Gemini, Llama, LangChain, LangGraph, AutoGen, MCP, RAG, SFT fine-tuning, LLM evals, PyTorch (Lightning, TorchServe), TensorFlow, scikit-learn, OpenCV, YOLO, ViTs, Spark Languages and Web: Python, TypeScript, Bash, React/Next.js, Django Cloud and DevOps: AWS, GCP, Docker, Kubernetes, Terraform, Prometheus, Grafana, Git, CI/CD 📋 Services I Provide: • Agentic AI and multi-agent system development (MCP, tool calling) • RAG design, implementation, and evaluation • Custom LLM applications (chat, copilots, document and scientific AI) • LLM fine-tuning and eval pipelines • Computer vision model development and deployment • ML pipelines, MLOps, and cloud infrastructure • AI-powered lab, research, and workflow automation • Full-stack builds around AI features 🌟 What Sets Me Apart: I do the work myself: architecture, code, deployment, monitoring, documentation. As a startup co-founder and hackathon winner, I prototype fast, then harden what works into production systems with real evals and observability. 🤝 Working With Me: You work directly with me. Expect working code early, frequent demos, and clear async communication. San Francisco based (Pacific time), fully remote, open to short sprints and long-term engagements. Have an AI system that needs to get built? Send me the details and I will reply with exactly how I would build it. Keywords: AI Engineer, Machine Learning Engineer, GenAI, LLM, RAG, AI Agents, Agentic AI, MCP, LangChain, LangGraph, AutoGen, OpenAI, Gemini, Llama, Fine-tuning, SFT, LLM Evaluation, Prompt Engineering, Computer Vision, YOLO, Vision Transformers, PyTorch, TensorFlow, OpenCV, Python, TypeScript, Next.js, Django, AWS, GCP, Docker, Kubernetes, Terraform, MLOps, Health-Tech AI, Scientific AI, Lab Automation, Bioinformatics

Technical project management experience includes both software and hardware. Software examples are cloud-based SaaS, mobile, embedded, desktop, and client/server software for AI, LMS, EH&S, facility and food safety, auditing, IoT, and Industry 4.0 applications. AI specific experience includes hands on advanced data annotation and tagging, as well as managing junior team members performing these tasks and regular dedicated account Fortune 500 customer touch points with metrics reporting on the results. Hardware experience includes RFP’s, project execution, QA, documentation, logistics, packaging and labeling, BOM’s, part numbers, service and support strategy, and supplier and ODM management for POS, PC, peripherals, safety products, digital signage players, gateways, consumer electronics, kiosks, dataloggers, sensor solutions, and kitchen appliances. These products have included AC, DC, and battery power and include wireless technologies such as Wi-Fi, Bluetooth/BLE, Zigbee, and 3G/4G cellular. Account management capabilities include developing ground-up solutions for new and existing enterprise customers, post sales activities for project execution, on-boarding and deployments, and ongoing sustaining activities such as system status, KPI reporting metrics, product defects, change requests, billing, licensing, MSA's, SOW’s, and up-sells. Regulatory and safety management includes worldwide certifications such as electronics regulated by the FCC, CE, IC, NOM, RCM, UKCA, KC, CB reports, UL, ETL, and all other NRTL certifications, DoC's, consumer goods regulated by the CPSC, CPC's, GCC's, state label laws, FDA Class 1 devices, lasers, cosmetics, textiles, MOCRA, FTC, REACH, RoHS, EU GPSR, CE-RED, WEEE, GCF, PTCRB, AT&T Network Ready, OSHA, California Proposition 65, CPG, textiles, MDF and EPA TSCA Title VI compliance, battery usage and shipment regulations, environmental stewardship, Reese’s law/Public Law 117-171, de minus imports, conflict minerals and 3TG, 16 CFR 1263, worldwide Amazon seller requirements, and Amazon de-listing research and appeals related to regulatory matters.