Associate Executive Director

About the role

A Glimpse of the Job
As the Director of AI and Data-Intensive Computing (Associate Executive Director), you will shape the future of AI, machine learning, and data-driven research at Texas A&M. In this pivotal leadership role, you’ll help drive the strategic vision for a nationally competitive center in computational and data-enabled science, working closely with the HPRC Executive Director to guide operations, set direction, and elevate the university’s research capabilities.

Responsibilities

• Lead and mentor the AI development and support team in building robust, scalable solutions and enabling HPRC users to use those technologies.
• Empower faculty and researchers to integrate AI capabilities into their applications and systems.
• Direct the development of custom AI agents and applications that solve specific campus needs.
• Establish and lead Machine Learning Operations practices, focusing on the continuous monitoring, tuning, and management of models in production.
• Develop AI literacy training material and lead the training effort.
• Support departments and colleges in integrating AI literacy across disciplines.
• Drive the adoption of AI and data-intensive technologies across Texas A&M research enterprise.
• Act as a subject matter expert, communicating the value and application of AI and machine learning to varying audiences.
• Provide recommendations to Executive Director for fiscal, personnel, administrative, and technical matters.
• Develop a comprehensive AI and data science roadmap, identifying high-impact opportunities across research and academic functions.
• Engage with campus leaders and teams to understand their challenges and help them envision what’s possible with AI and data.
• Establish performance indicators, metrics, and benchmarks to measure the impact of AI-related initiatives.
• Stay current on the latest advancements in machine learning, data science, and generative AI, evaluating their potential to solve the unique challenges the HPRC users face.
• Serve as the primary leader for AI and data-intensive projects and develop training materials for end users.
• Lead and participate in research projects as Principal Investigator (PI) or Co-PI or Senior Personnel funded by funding agencies.
• Facilitate awareness and use of partner programs such as NSF ACCESS and NAIRR.
• Represent HPRC in local, regional, national, and international initiatives with a high degree of professionalism.
• Participate in the VISION project and other AI initiatives from Texas A&M University System.
• Supervise assigned staff, empowering the team to make decisions, take ownership of their work and grow their skills.
• Act as a coach and mentor, helping the team members overcome obstacles and achieve their professional goals.

Qualifications

• Bachelor's Degree or any equivalent combination of training or experience.
• Ten years’ progressively responsible experience in AI Data Science, Computing Engineering, Information Systems, or a related field, and five years of supervisory experience.
• A Ph.D. in Computer Science, AI, Data Science, Computer Engineering, Information Systems, or a related field.
• Experience working in supercomputing center at a higher education or public sector environment.
• Experience implementing data lakes, lake houses, or mesh architectures, data governance best practices.
• Certifications in AI/ML, cloud architecture, or data integration tools.
• Experiences in evaluating emerging AI technology programs, defining benchmarks, and scaling best practices.
• Strong programming skills in Python, R, SQL, C++, and experience with modern AI/ML frameworks like TensorFlow, PyTorch.
• Strong technical understanding of AI technologies, data analytics tools, and platforms.
• Deep understanding of large language model, large foundation model, data architecture, data modeling, pipelines, and warehousing in a complex HPC environment.
• Experience with commercial cloud platforms and services (e.g., AWS, Azure, Google Cloud), especially those used for AI and data-intensive processing.
• Demonstrated experience in AI & ML solution development, data engineering, enterprise-level data, and data-intensive technologies.
• Exceptional leadership, communication, and stakeholder engagement skills.
• Expert knowledge of data management systems, practices and standards.
• Ability to occasionally work outside of normal working hours and weekends, may require some domestic travel.