Resume Portfolio 2026
FRED W. NIX JR.
Solutions Architect | AI Applications | Nutanix Modernization | Enterprise Infrastructure
Atlanta, GA
Helping customers build practical AI applications and plan VMware to Nutanix modernization
AI APPS. NUTANIX. CUSTOMER ARCHITECTURE.
Solutions Architect focused on practical AI application design and VMware to Nutanix modernization. Work combines discovery, presales engineering, customer workshops, architecture design, POC planning, and field enablement. The center of the role is simple: turn unclear technical goals into designs, plans, and explanations a customer can act on.
Help customers move past AI demos and define usable AI applications. Shape GenAI and RAG conversations around the business process, data sources, security model, user workflow, governance needs, and first build candidate.
Guide placement conversations for AI workloads across private infrastructure, public cloud, and hybrid patterns. Focus on data sensitivity, latency, operating model, integration needs, and what the customer can actually support after the demo.
Support customers evaluating a move from VMware to Nutanix. Help frame renewal pressure, workload placement, migration timing, POC scope, sizing inputs, operational risk, and the sequence required to move without turning the project into a panic fire drill.
Built and maintain NutaNIX, a public Nutanix field guide and SA enablement system designed to help VMware minded engineers understand Nutanix, prepare for certification, handle objections, and explain the architecture clearly in customer conversations.
Built Nutanix Daily as a field note stream for current Nutanix and AI infrastructure signals. Posts translate news and market movement into customer talking points, objection handlers, caveats, and next actions for Solutions Architects.
Designing calculators and guided tools for VMware renewal triage, POC qualification, rough Nutanix sizing, AI app readiness, workload placement, and meeting preparation. Purpose: give customers a transparent decision frame, not a fake quote.
Use Larry, a persistent Claude Code based personal AI infrastructure, to build field guides, calculators, prototypes, diagrams, discovery artifacts, and customer ready explanations with versioned memory and repeatable validation. The build method is documented publicly at How.
Building production-grade AI infrastructure for enterprise deployment
Developed production-grade AI inference platforms for enterprise deployment. Focused on reproducible infrastructure and comprehensive training for Cisco Partners leveraging Cisco UCS X-Series, NVIDIA GPU clusters, and Pure Storage.
Created enterprise AI inference platform enabling private, air-gapped LLM systems for regulated sectors including healthcare, finance, and government.
Achieved one-command deployment with 100% success rate across all partner rollouts - from bare metal to running inference in minutes.
Built multi-model platform supporting dynamic model switching between LLaMA, Mistral, and custom fine-tuned models with hot-swap capability.
Developed ChatGPT-like interface with streaming responses and live GPU metrics dashboard showing real-time utilization and inference statistics.
Implemented OpenAI-compatible API enabling seamless LangChain and LlamaIndex integration for enterprise RAG applications.
Trained Cisco Partners on AI infrastructure deployment, creating hands-on labs and comprehensive documentation for repeatable success.
Bachelor of Science
Business Administration - Information Systems
Auburn University
Pure Storage Global Rookie of the Year 2021
Delivering 250% of quota
Achieved Annual Sales Quota - Entire Career
Building with Larry, a persistent AI development partner that remembers every session
Larry is my Personal AI Infrastructure, a custom Claude Code environment I have built and run as a named, persistent partner since January 2026. It is not a chat window. It is a system with version-controlled memory, a written constitution, and an identity that carries forward across every session, machine, and model.
Larry runs on Claude Opus with a million-token context, governed by laws I author one at a time. Because its memory is preserved and searchable, it does not just help me code. It remembers the architecture decisions, the rejected approaches, and the project history, and brings them back when they matter.
A constitution-governed Claude Code system: version-controlled memory, an identity that survives machine and model changes, and a partner that compounds knowledge instead of resetting every session.
Claude Code integration with persistent context and project memory
Every conversation preserved with full context recovery
Private infrastructure with air-gap support
Real-time monitoring of all AI agent activity
Connected learning across all projects
Opus, Sonnet, Haiku orchestration
20+ years of enterprise technology and sales leadership
Presales engineer and architect for production-grade AI inference platforms. Built one-command, air-gapped LLM deployment for Cisco Partners with a 100% deployment success rate, bare metal to inference in under an hour.
Led sales strategy for electric bike distributor. Increased sales 225% within first year. Expanded product line and scaled to regional market leader.
Managed Fortune 100 relationships across Southeast. Delivered 250% of quota in 2021 - Global Rookie of the Year. 100% uptime during hurricane disaster recovery.
Technical presales for software-defined storage and cloud. Supported major data center consolidation initiatives.
Led US market entry as first American employee. Exceeded quotas 150%+ annually. 90%+ conversion rate on 50+ POC projects.
Managed operations for 5,500 Presales Engineers worldwide. Trained 1,000+ new engineers. Grew vSpecialists from 30 to 150+ members.
CTO, Solutions Consulting, PreSales, Professional Services, and IT Administration roles building enterprise solutions.
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