Senior Enterprise Architect - AI

Job Title

Senior Enterprise Architect - AI

Agency

Texas A&M University System Offices

Department

Chief Information Officer

Proposed Minimum Salary

Commensurate

Job Location

College Station, Texas

Job Type

Staff

Job Description

The System Offices is one of several system members within the Texas A&M University System representing one of the largest systems of higher education in the nation, with a network of 12 universities, a comprehensive health science center, nine state agencies, and the RELLIS Campus. The Texas A&M University System mission is to provide education, conduct research, commercialize technology, offer training, and deliver services for the people of Texas and beyond.

The System Offices, within the Texas A&M University System, provides an outstanding benefits package including, but not limited to: competitive health benefits; paid vacation, sick leave, and holidays; a defined benefit retirement plan to include an employer contribution through Teachers Retirement System of Texas (TRS); if applicable, a defined contribution retirement plan to include an employer contribution through an approved ORP vendor: additional voluntary tax deferred annuity (TDA) options; tuition assistance; and wellness programs to promote work/life balance.

Salary:

Commensurate with experience.

Job Description Summary:

The Senior Enterprise Architect - AI is responsible for role will work under the direction of the Executive Director, Enterprise Architecture and work closely with the OIT leadership team and staff members in developing AI solutions for the system office and for its members.

Responsibilities:

AI Strategy and Enterprise Architecture

- Working under the direction of the Executive Director, Enterprise Architecture, develop, maintain, and communicate a comprehensive AI and machine learning architecture strategy and multi-year roadmap aligned with the Texas A&M University System’s institutional mission, strategic priorities, and digital transformation goals.

- Define and enforce enterprise architecture standards, reference architectures, design patterns, and governance frameworks for AI/ML solutions across the System Office and member institutions.

- Evaluate emerging AI technologies, platforms, and methodologies; conduct feasibility assessments and proof-of-concept initiatives to determine applicability and readiness for enterprise adoption.

- Advise the Executive Director of Enterprise Architecture and OIT leadership on the strategic integration of AI capabilities into the System’s technology portfolio, including build-versus-buy analyses and total cost of ownership assessments.

AI Solution Design and Implementation

- Architect end-to-end AI/ML solutions—including data pipelines, model training and validation workflows, deployment infrastructure, and monitoring systems—ensuring scalability, reliability, security, and reproducibility.

- Design and oversee the implementation of generative AI, large language model (LLM), natural language processing (NLP), agentic AI, and intelligent automation solutions that address administrative, academic, and research use cases across the System.

- Collaborate with data architects, software engineers, infrastructure teams, and data scientists to ensure AI solutions integrate seamlessly with existing enterprise platforms (e.g., ERP, CRM, LMS, research computing environments).

- Establish and promote MLOps best practices, including CI/CD pipelines for AI models, automated testing and validation, model versioning, drift detection, retraining protocols, and lifecycle management.

Cross-Institutional Collaboration and Stakeholder Engagement

- Serve as a primary technical liaison between the System Office, member institution CIOs, IT leadership, and faculty researchers on the development and deployment of common AI solutions and shared services.

- Engage with faculty members who research, use, and apply AI to identify collaborative opportunities, align institutional AI initiatives, and ensure enterprise architecture supports the academic and research missions.

- Facilitate cross-functional architectural discussions, workshops, and working groups to build consensus, awareness, and alignment around AI strategies and technology standards across the System.

- Translate complex technical AI/ML concepts into clear, accessible communications for executive leadership, non-tech