About

Master's-educated AI/ML researcher and architect with 168+ published models and 97+ datasets (HuggingFace) and 23+ years of cross-disciplinary expertise in cloud, virtualization, and storage engineering.

Designs and ships production-grade agentic AI systems—multi-agent orchestration, MCP integrations, Agentic RAG—at a pace traditional development cycles rarely allow, alongside scalable infrastructure (NetApp, AWS, Kubernetes).

Combines technical depth with leadership in disaster recovery, DevOps, and systems architecture.

Experienced and passionate Unix engineer and architect.

Areas of Interest

Agentic AI:

Multi-agent orchestration (planner/executor/critic patterns), MCP server development, context/memory management for long-running agent sessions, graph-based autonomous research pipelines, cost/latency/model-selection tradeoff evaluation

AI/ML:

Model development (PyTorch, TensorFlow), fine-tuning & quantization (GGUF, LoRA/Unsloth), RL, Bayesian analysis, time-series forecasting, edge AI deployment

Architecture:

MCP, LangChain, Embeddings, Agentic RAG, Traditional Systems Architecture, Time-series analytics, Data pipelines, Data lakes

Cloud/Infra:

AWS/GCP/Oracle Deployments and Management, Docker, VMware, Kubernetes,NetApp SAN/NAS, EMC

DevOps:

Ansible, CI/CD pipelines, logging/alerting strategies, Python/Bash scripting

Systems:

Linux (Ubuntu, RHEL, Debian), Windows, Solaris, Embedded

Storage:

NetApp SAN/NAS, EMC

Disaster Recovery:

NetApp Snap Manager, Ops Manager, SnapMirror, SnapVault, EMC VMAX Replication

Virtualization:

VMware vCenter, vSphere, vCenter Orchestrator

Container Orchestration:

Kubernetes, Docker Swarm, Docker Compose

Database Engineering:

Oracle, SQL Server, MySQL, PostgreSQL

CI/CD:

Circle CI, GitLab CI, GitHub Actions

Experience

Technology Architect & Systems Engineer | Tatman Technologies | Jan 2012 – Present

Deliver AI/ML consulting for SMBs: train edge-optimized models, deploy time-series analytics, and design Agentic RAG workflows. - Architect hybrid cloud storage (NetApp → AWS S3) and DevOps pipelines (logging/notification systems). - Refactor Python scripts for critical infrastructure; optimize I/O performance in distributed systems.

Storage Engineer | Contracting for Odyssey Information Services | Dec 2010 – Jan 2012

Managed 60+ NetApp/EMC arrays across dev/prod; designed multi-node Ops Manager monitoring. Led data migration/orchestration for Oracle/SQL/VMware workloads using Snap Manager.

Chief Technologist | Tatman Technologies, Inc. | Sep 2009 – Jan 2010

Private Contracting for clients in the Technology Space. Container orchestration, Storage Architecture, DevOps Consulting

Senior UNIX/Storage Engineer | Sun America (AIG) | Jul 2003 – Sep 2009

Oversaw 9PB+ storage (NetApp/EMC DMX) and 250+ UNIX servers; standardized NetApp tools via Ops Manager. - Pioneered disaster recovery templates for Unix and NetApp Storage, reducing recovery time by 40%.

Education

Masters in Machine Learning, Colorado State University Global (2025)
BS in Computer Science & IT, Colorado State University (2022)
OS Design, Denver Institute of Technology (1999)

Projects

Models & Data (huggingface.co/jtatman): 168+ models, 97+ datasets — fine-tuned LLMs (Qwen, Llama, Phi), GGUF quantization, curated instruction/psychology datasets
Code (github.com/jtatman):
- HegelianAI: multi-LLM dialectical refinement engine (thesis→antithesis→synthesis) for iterative idea refinement across agents
- grand-bible: semantic/archetype correlation analysis across aggregated mythological & religious texts
- skills-registry: on-demand semantic-router skill loader for agent frameworks, reducing context overhead
- socket-ai: collaborative multi-bot LLM environment with real-time monitoring
- sepolia-testnet-simulator: on-chain DeFi simulator (trading, DAO, gaming, Chainlink price feeds)
Experiment Tracking (wandb.ai/jtatmanus): quantized small-model fine-tuning runs

Contact

storagearchitect at live dot com

Resume