SVP, Data & AI Strategy and Transformation

Arlington, VA

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Kapitus is seeking a Senior Vice President, Data & AI Strategy and Transformation to serve as the Chief Data and AI Officer's principal leader for enterprise Data & AI architecture, transformation execution and technical delivery. Reporting to the CDAO, the SVP will translate and execute Kapitus' approved enterprise Data and AI vision to sequenced target state architecture, operating mechanisms, investment roadmap, reference patterns, and measurable transformation outcomes.

The SVP will lead the practical conversion of fragmented data, workflows and point solutions into trusted enterprise data, reusable intelligence, governed automation, and measurable business outcomes. This is a player-coach role for a leader who move fluently between executive decision making and technical implementation. Will be advising the CDAO on material choices while remaining directly engaged in architecture, prototyping, design assurance, and delivery.

What you will do:

Strategy and Operating Model

• Lead the development and execution of the enterprise Data and AI strategy for CDAO and Executive team approval by translating corporate priorities in sales, credit, risk, finance, and operations—into a sequenced transformation plan with clear outcomes, milestones, investments, and executive decision points.
• Design, operationalize and continuously improve the Data and AI operating model including decision rights, product ownership, domain accountability, architecture governance, responsible-AI controls, funding, and value realization — and advise the CDAO and executive leadership on trade-offs, sequencing, vendor choices, and platform economics.

Enterprise Data Architecture and Data Products

• Design and implement the enterprise data architecture — data-fabric capabilities (metadata-driven integration, active lineage, policy enforcement, discoverability) with data-mesh principles (domain ownership, product thinking, federated governance) on a layered Lakehouse/medallion foundation — with reference architectures, standards, data contracts, and guardrails spanning integration, APIs, orchestration, metadata, data quality, master data, semantic and knowledge models, ML/AI, security, observability, and Fin Ops.
• Enable VP of Data Products to prioritize and lead data products from concept through production adoption — named owners, defined consumers, source contracts, quality thresholds, lineage, service levels, and lifecycle controls — serving certified BI, APIs, events, files, machine-learning features, and AI context.
• Provide hands-on leadership in data modeling, SQL and transformation design, orchestration, testing, observability, and production-readiness reviews, replacing duplicate pipelines, reports, and point solutions with governed, reusable products.

Agentic AI Platform and Orchestration

• Define…