Chief Data & Artificial Intelligence Officer

Texas Capital•Dallas, TX

22h

About The Position

The Chief Data & AI Officer will execute the data and artificial intelligence strategy across Texas Capital. This role leads the enterprise data and AI strategy, platform, and governance framework, overseeing a team of approximately 100 full-time employees and contractors (40 FTE) spanning data engineering, AI/ML infrastructure, and data governance functions. Reporting directly to the Chief Digital & Information Officer, this executive is responsible for making the bank's data trustworthy, usable, and productive, while turning AI into a governed, repeatable enterprise capability rather than a collection of disconnected experiments. The role requires deep technical fluency across modern data platforms (Kafka, SQL Server, Postgres, Snowflake, Calibra) and emerging AI technologies (agentic systems, LLMs, AI security, AI gateways and guardrails), paired with the executive presence to partner with line of business leaders, technology peers, and the Board.

Requirements

15+ years of progressive experience in data, analytics, or AI leadership, including 8+ years managing large, multi-disciplinary teams (50+ employees)
Advanced degree in Computer Science, Data Science, Engineering, or related field preferred
Deep experience in data platforms, governance, and analytics within complex, regulated environments such as financial services
Hands-on fluency with modern data infrastructure: Kafka or equivalent event-streaming platforms, SQL Server, Postgres, and cloud data warehouses such as Snowflake
Demonstrated experience governing or deploying AI/LLM technologies, including AI security, AI gateways, and guardrail frameworks
Proven track record setting enterprise data and AI strategy and translating it into a funded, prioritized roadmap
Experience running cross-functional governance bodies (e.g., data councils) and arbitrating competing business priorities
Strong track record of regulatory and compliance exposure (e.g., SOX, data privacy) in a banking or financial institution
Executive-level communication skills, with experience reporting to executive committees and Boards
Experience with data cataloging and governance tools such as Calibra
Background in agentic AI systems and emerging generative AI architectures
Prior experience operating in a first-line role with second-line risk oversight (e.g., partnering with a Chief Risk Officer on data and model risk)
Experience building or scaling a data/AI organization through a major technology transformation or operating model change

Responsibilities

Refine and own the enterprise data and AI strategy, roadmap, and investment case
Hold accountability for data governance and AI governance across the firm
Run the Executive Data & AI Council, arbitrating cross-line-of-business definitional and prioritization disputes
Define the operating model with lines of business, including domain ownership, stewardship, and data products
Report enterprise data quality, AI risk posture, and realized value to the executive committee and Board
Own the enterprise data and AI platforms, spanning streaming (Kafka), transactional databases (SQL Server, Postgres), cloud data warehousing (Snowflake), and data cataloging (Calibra)
Lead development of AI infrastructure supporting LLM deployment, agentic technologies, and generative AI use cases
Establish and enforce AI security standards, including AI gateways and guardrails to govern model access, usage, and risk exposure
Drive architectural alignment with the Chief Technology Officer and shared infrastructure teams
Oversee capacity planning, platform reliability, and cost management across the data and AI estate
Own AI use-case intake, prioritization, and delivery in partnership with Divisional CIOs, product teams, and lines of business
Ensure AI initiatives are delivered with measurable business value, appropriate risk controls, and regulatory compliance
Partner with product and business leaders to identify high-value opportunities for agentic technologies and LLM-driven automation
Establish a disciplined framework for piloting, scaling, and retiring AI use cases across the enterprise
Build, lead, and develop a team of approximately 100 full-time employees and contractors (40 FTE) through four direct reports
Attract and retain top data and AI talent, establishing a culture of accountability, innovation, and operational excellence
Mentor senior technical leaders to build organizational depth and succession readiness
Manage a multi-million-dollar technology and talent budget with discipline and transparency