Director, Enterprise Architecture

Servco•Honolulu, HI

About The Position

The Director, Enterprise Architecture translates AI and data strategy into practical business process, application, integration, data, AI, and technology designs for Hawaii Mobility. Reporting to the VP, Data & AI, the role guides target architectures and transition roadmaps that strengthen customer relationships, connect customer journeys, and improve daily operations. The role’s design authority centers on Hawaii Mobility and partners with Australia mobility, music, and investments where shared capabilities make sense. The Director leads the Data & AI Architect and works with operators and delivery teams to redesign workflows and connect digital and physical experiences. The role runs a lean architecture practice that listens first, establishes clear guardrails and reusable paths, learns quickly from production, and helps teams adopt change at a practical pace. The Director translates Servco Digital Strategy principles—Omnichannel Integration, Datafication, and Tech Modernization—into connected customer journeys, governed 360 data, and simplified, open, cloud-native target architectures. The role maintains small, actionable reference patterns informed by production learning; applies Problem Led, Highly Automated, and Talent Driven principles; and uses risk-tiered reviews, brief decision records, supported build paths, and local decisions within guardrails. It listens to frontline teams and leaders, maps customer journeys, business processes, capabilities, and system dependencies, identifies root constraints, tests assumptions, and designs practical transitions. The Director advises the VP, Data & AI on tradeoffs and outcomes. The role designs how predictive AI, generative AI, agents, and automation fit operational workflows. It establishes reusable patterns for model selection, governed retrieval and context, scoped tool and API access, agent orchestration, human handoffs, and enterprise application integration. It architects identity, permissions, approvals, traceability, evaluation, monitoring, fallback, and recovery for AI-assisted decisions, and turns NIST AI RMF, its Generative AI Profile, and ISO/IEC 42001 concepts into practical risk controls. It establishes MLOps and LLMOps patterns from experimentation through production, including versioned data, models, prompts, and tools; automated tests and releases; offline and live evaluation; tracing; drift and safety monitoring; rollback; and iteration. It tracks quality, latency, cost, adoption, and business outcomes. The Director shapes application and integration architecture across APIs, events, services, and the system portfolio, connecting discovery, vehicle inventory, trade, financing, sales, logistics, delivery, service, and support. It aligns process changes and data flows across digital and in-person touchpoints; defines shared data models and contracts for customer identity and consent, vehicles, inventory, transactions, service, and finance; and guides trusted 360 data products and Databricks/Azure architecture with ownership, quality, lineage, privacy, access, and semantic definitions. The role partners with Technology Infrastructure & Security on resilience and cost. The Director develops the Data & AI Architect and aligns engineers and delivery teams through practical design reviews. It pairs with operators to test patterns in real work, teaches rather than prescribes, invites feedback, shares credit, and turns successful designs into supported build paths. It partners with architecture and technology leaders across Australia mobility, music, and investments on compatible patterns and reusable solutions while respecting each business’s decision rights. The role communicates dependencies, risks, costs, and choices clearly to business and technical leaders.

Requirements

Bachelor’s or Master’s degree in a related field, or equivalent demonstrated experience.
10–15 years of enterprise architecture experience with hands-on depth across application, integration, data, and process architecture, and the ability to connect these areas to business capabilities, AI, and infrastructure.
Production AI and automation architecture experience, including MLOps and LLMOps, governed tools and data, evaluation, observability, security, reliability, cost, and measurable business impact.
Experience in vertically integrated manufacturing, distribution, retail, automotive, or adjacent operations, connecting strategy, customer and operator needs, target designs, and practical transition plans.
Databricks and Azure experience, including Unity Catalog, Delta Lake, and lakehouse patterns.
Strong systems thinking and first-principles problem-solving skills, including tracing end-to-end causes, challenging inherited assumptions, and simplifying designs while balancing customer experience, operating realities, security, resilience, and cost.
Ability to guide cloud modernization and lean architecture decisions with engineers and operators.
Ability to listen with humility, explain tradeoffs clearly, develop architects and delivery teams, and help operators adopt change at a realistic pace.

Nice To Haves

Experience influencing shared architecture across the US and Australia.
Experience applying responsible AI guidance to production decisions.
Experience with connected omnichannel retail and customer journeys.

Responsibilities

Translate Servco Digital Strategy principles into connected customer journeys, governed 360 data, and simplified, open, cloud-native target architectures.
Maintain actionable reference patterns and apply practical architecture governance, including risk-tiered reviews, decision records, supported build paths, and local decisions within guardrails.
Listen to frontline teams and leaders; map customer journeys, processes, capabilities, and system dependencies across sales, service, and fulfillment.
Use systems thinking and first-principles problem solving to identify root constraints, test assumptions, and design practical transition roadmaps.
Advise the VP, Data & AI on architecture tradeoffs and outcomes.
Design how predictive AI, generative AI, agents, and automation fit operational workflows.
Establish reusable AI patterns for model choice, governed retrieval and context, scoped tool and API access, agent orchestration, human handoffs, and enterprise application integration.
Architect identity, permissions, approval points, traceability, evaluation, monitoring, fallback, and recovery for AI-assisted decisions.
Translate NIST AI RMF, its Generative AI Profile, and ISO/IEC 42001 concepts into practical risk controls.
Establish MLOps and LLMOps practices for versioned assets, automated testing and releases, evaluation, tracing, monitoring, rollback, and iteration; track quality, latency, cost, adoption, and business outcomes.
Shape application and integration architecture across APIs, events, services, and the system portfolio, connecting customer and operational processes across the mobility lifecycle.
Define shared data models and contracts for customer identity and consent, vehicles, inventory, transactions, service, and finance.
Guide trusted 360 data products and Databricks/Azure architecture, including ownership, quality, lineage, privacy, access, and semantic definitions.
Partner with Technology Infrastructure & Security on resilience and cost.
Lead and develop the Data & AI Architect and align engineers and delivery teams through practical design reviews.
Work with operators to test patterns, gather feedback, support adoption, and turn successful designs into supported build paths.
Partner with architecture and technology leaders across Australia mobility, music, and investments on compatible patterns and reusable solutions while respecting decision rights.
Communicate dependencies, risks, costs, and choices to business and technical leaders.