Chris Hudson
Director of Software Engineering @Chhj Franchising Llc
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WORK HISTORY
Director of Software Engineering @Chhj Franchising Llc
Tampa, FL, US
Reengineered SDLC and delivery model with automated change management and GitHub Actions–based CI/CD, creating clear protocols for design reviews, code quality, and deployment readiness while maintaining PCI, GDPR, and NIST compliance.Leading migration to AWS cloud-native, redesigning a legacy platform into containerized, event-driven microservices to improve scalability, resilience, and readiness for AI-driven capabilities.Implemented an analytics backbone with AWS Redshift and Glue-based ETL, enabling scalable reporting and future AI/ML use cases for a 200+ franchise network.Scaled the engineering org from 9 to 15 engineers (US + offshore), establishing engineering KPIs (velocity, MTTR, deployment frequency) and coaching teams toward higher performance and predictable delivery.Introduced GitHub Copilot with supporting governance and playbooks, shaping AI-assisted development while maintaining code quality, safety, and compliance.
EDUCATION
University of South Florida
BA, Sociology
University of South Florida
BA, Psychology
SKILLS
ABOUT CHRIS HUDSON
I lead AI Engineering Excellence for large-scale organizations, building standards, operating models, and communities of practice to drive enterprise-grade AI delivery.With 15+ years in engineering leadership and 5+ years in AI/GenAI, I\'ve transformed Fortune 100/50 enterprises and high-growth companies: establishing AI Centers of Excellence and GenAI Advisory practices, modernizing SDLC/release engineering for a 300-app platform (Amex), and leading platform/SRE for high-volume global e-commerce.My expertise spans AI engineering, governance, and delivery rigor:AI CoEs & Communities of Practice: Defining AI engineering standards, playbooks, and reusable patterns for predictable, safe AI delivery.Business-to-Technical Translation: Guiding AI solution design aligned with enterprise architecture, data platforms, and regulatory compliance.MLOps/LLMOps-Inspired Engineering: Applying CI/CD, testing, observability, safety/RAI checks, and production readiness to AI/GenAI solutions.Lifecycle Integration & Governance: Partnering with portfolio/program operations on OKRs, capacity planning, cross-team dependencies, and engineering protocols.Enablement & Training: Raising AI literacy across engineering and business stakeholders via training, masterclasses, and technical documentation.Key Outcomes:Built GenAI Advisory & AI CoE, defining AI standards/governance, contributing to a mid–seven-figure pipeline (Fortune 100/50 clients).Standardized SDLC/release engineering for a 300-app platform (Amex), moving from 4 releases/year to deployments every 10 days; reduced incidents ~30% while maintaining PCI compliance.Led platform/SRE for global e-commerce, achieving 99.99% uptime, reducing P1 incidents from 5/month to 0 over 12 months, enabling safe daily deployments, and cutting IT spend ~$300K/year.Delivered GenAI/Responsible AI training, increasing AI tool adoption ~20% and fostering common understanding for AI experimentation/productization.Interested in roles like AI Engineering Excellence Lead, Head of Applied AI Engineering, Head of AI/GenAI Platform, or VP of Engineering Excellence to build scalable, compliant AI delivery capabilities.Core competencies: AI & GenAI delivery, AI CoEs & Communities of Practice, MLOps/LLMOps, SDLC modernization, DevSecOps, SRE & observability, governance & compliance (NIST, PCI, GDPR), technical leadership, cross-functional stakeholder management.
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