The hardest part of leading retail technology in 2026 is not picking the right platform; it is sequencing platform decisions so that store, e-commerce, OMS, data, and security architectures stop fighting each other. That is the work I want to do at Claire's.

My background is operational, not theoretical. Thirty years of architecting and running enterprise stacks - Microsoft 365, SharePoint (2010 through Online), Salesforce, HubSpot, Lightspeed-class POS evaluations, Shopify/BigCommerce assessments, OMS and fulfillment integrations, Azure and AWS - gives me a working library of how these systems break and how they hold together at scale. I can read a five-vendor architecture diagram and tell you within an hour where the failure modes are.

A few specifics relevant to the JD's domain matrix:

• Retail systems & omnichannel. I have led platform unifications integrating point-of-sale data, inventory visibility, and customer profiles into single-source-of-truth analytics. Healthcare's matrix of 5,000-user collaboration platforms, M&A consolidations, and zero-downtime migrations is not a literal Claire's POS environment, but the operational pattern transfers directly.
• Cloud and modernization. Multi-year programs across Azure, AWS, and GCP. Container orchestration with Docker, Kubernetes, Terraform, Ansible, ArgoCD. CI/CD pipelines, microservices, API strategy, legacy decommission. Co-authored a SharePoint migration toolset using Portainer, Balena, and Kubernetes that reduced migration cycle time meaningfully.
• Data, analytics, and AI. Power BI executive dashboards on Salesforce and ERP data. Azure Data Warehouse for unified reporting. Most recently, I built an AI adoption program that embedded context-engineering and prompt-engineering frameworks with measurable KPIs across an engineering organization. For Claire's specifically, the sequencing is non-negotiable: operational decision-making AI first (forecast, optimize, propose, human review, execute, learn for inventory and assortment, targeting forecast error below 15% against a 25-30% baseline), generative AI second, and only after the data spine has earned the right to scale it.
• Cybersecurity and resilience. Led a 60-day ransomware recovery - incident response, threat-actor negotiation, forensic containment, full re-architecture. PCI, SOC 2, HIPAA, Zero Trust, IAM, MFA, SSO are part of how I design, not a separate workstream.

I do not believe a CTO should ship a single tool decision in the first thirty days. I believe a CTO should ship a single architecture decision - one that frees the next twelve months of engineering work from compounding tech debt. At Claire's, that decision is to retire Salesforce CRM and Salesforce Commerce Cloud in favor of HubSpot as the single revenue brain, Shopify or BigCommerce on the front end, Lightspeed Retail at the till, and Azure underneath, with the merchandising AI loop running on top. The TCO advantage is 50-60% at retail scale, and more importantly the architecture stops fighting itself: omnichannel becomes possible, decision-making AI becomes possible, and the rest of the 18-month plan stops being aspirational. I would welcome the chance to walk through the dependency map and the cutover sequencing in detail.

Respectfully,