A deeper look at the roles, programs, capabilities, and outcomes I've delivered across Generative AI, Agentic AI, Azure cloud, Industrial IoT, and digital transformation for Fortune 500 organizations and the public sector.
From hands-on engineer to Chief AI Officer — a continuous arc of building, scaling, and advising on enterprise AI and data platforms.
Global Professional Services · Enterprise & Public Sector
Innovation evangelist and end-to-end architect for ambitious enterprise AI programs. Advise C-suite on AI strategy, operating models, and Centers of Excellence. Lead solution architecture for Generative AI, Agentic AI, large-scale ML, Industrial IoT, and modern data platforms across Microsoft, open-source, and multi-cloud ecosystems.
Azure AI / ML Practice Leadership
Built enablement pathways, productionized ML workflows, and led the Azure AI/ML practice — accelerating ROI through standardized accelerators, reference architectures, and reusable solution patterns.
Manufacturing, Energy, Building Technology & Sustainability
Designed edge-to-cloud platforms for connected factories, predictive quality, digital twins, and computer vision on NVIDIA Jetson — bridging OT and IT to drive measurable productivity gains.
Global enterprise programs
Designed real-time insight platforms serving 10,000+ global retail sites, supply chain optimization, and decision-acceleration solutions — embedding security, governance, and observability from day one.
UW Milwaukee CSI · Purdue Indiana · NSF / Manufacturing USA
Industry Advisory Board member, NSF proposal contributor, and university course designer. Author of three books on enterprise AI and an international keynote speaker on Agentic AI, Azure OpenAI, Responsible AI, and AI in Manufacturing.
A T-shaped operator: deep in AI/ML and cloud architecture, broad across data, security, IoT, and program leadership.
Model lifecycle, retrieval, guardrails, prompt governance, evaluation and telemetry for production-grade generative systems.
Multi-agent orchestration on Microsoft Foundry, tool use, planning, memory, and human-in-the-loop patterns.
Distributed fine-tuning of LLaMA, Mixtral, Qwen on A100 / H100 / H200 clusters with vLLM, ONNX, and NVIDIA NIM.
Edge-to-cloud ingestion, time-series analytics, predictive maintenance, computer vision on Jetson, digital twins.
Lakehouse, medallion layering, MLOps, semantic modeling, and end-to-end governance frameworks.
Zero trust patterns, secretless design, policy-as-code, RBAC least privilege, and Responsible AI guardrails.
Portfolio shaping, cross-functional alignment, value realization, and risk mitigation across global delivery teams.
From PoC to scalable MVP, adoption patterns, CoE enablement, and reusable solution accelerators.
Workshops, keynotes, executive briefings, and CoE design that align leadership and accelerate AI adoption.
A side-by-side view of how my role evolved as enterprise technology shifted — from on-prem data warehouses and early cloud, through big data and ML, into Generative AI and today's Agentic AI systems.
Started building enterprise applications, SQL data warehouses, BI reports, and integration pipelines for Fortune 500 customers.
SQL Server, SSIS/SSAS/SSRS, .NET, Java, SOA. Reporting and OLAP cubes powered enterprise decisions.
Moved into solution design — building data platforms, custom analytics, and early cloud lift-and-shift programs for global enterprises.
Azure and AWS emerge. Virtualization, IaaS, mobile, and HTML5 reshape delivery. Hadoop unlocks "big data."
Designed Hadoop/Spark lakehouses, real-time streaming, and IoT ingestion platforms. Began leading multi-disciplinary delivery teams.
Hadoop, Spark, Kafka, Cassandra. IoT Hub, Event Hubs. Docker and Kubernetes start changing how we ship software.
Led classical ML and deep learning programs — predictive maintenance, computer vision, NLP — and connected-factory blueprints across manufacturing and energy.
TensorFlow, PyTorch, GPUs in the cloud. Azure ML, Databricks, MLflow. Edge AI on NVIDIA Jetson and OpenVINO.
Built and led the Azure AI/ML practice. Stood up MLOps reference architectures, Responsible AI patterns, and reusable accelerators across industries.
Transformer architectures mature. BERT, GPT-3, Stable Diffusion. MLOps becomes a first-class discipline. Synapse, Fabric, Cosmos DB scale.
Architected Azure OpenAI solutions for Fortune 500 customers — RAG platforms, copilots, document intelligence, and Responsible AI guardrails. Authored two books on enterprise AI.
Azure OpenAI, GPT-4, LLaMA, Mixtral. Vector databases, RAG, Semantic Kernel, LangChain. Microsoft Fabric and Copilot reshape productivity.
Lead enterprise Agentic AI strategy and Microsoft Foundry implementations. Architect distributed fine-tuning of 400B+ parameter models on H100/H200 clusters. Author of Agentic AI with Microsoft Foundry (2026).
Microsoft Foundry, multi-agent frameworks, reasoning models, vLLM, NVIDIA NIM. H100/H200/B200 clusters. AI becomes autonomous, tool-using, and observable.
Programs delivered across regulated and non-regulated industries — translating AI patterns into outcomes that fit each domain.
Selected programs and the value they delivered. Specific customer names protected by NDA.
| Program | Outcome | Value |
|---|---|---|
| Retail Insight Platform | Unified real-time operations & demand visibility | 10k+ stores |
| Manufacturing Predictive Quality | Defect & anomaly reduction with edge vision | Quality uplift & cost avoidance |
| Generative AI Advisory | Secure, governed AI adoption blueprint | Faster, safer innovation |
| Enterprise Data Program | Standardized, reusable ML pipelines | Time-to-insight reduction |
| LLM Fine-Tuning Platform | Distributed training on H100 / H200 clusters | 400B+ param models served |
| Industrial IoT Reference Architecture | Edge-to-cloud blueprint & digital twin | Reusable across plants |
| AI Center of Excellence | Governance, talent, accelerators, value tracking | Scaled enterprise adoption |
A working toolkit refreshed continuously as the AI and cloud landscape evolves.
Looking for an AI strategist, architect, or keynote speaker who can move from vision to working systems? Let's talk.