Associate Executive Director

Texas A&MCollege Station, TX
Onsite

About The Position

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. You’ll lead transformative initiatives that expand how AI and data inform discovery, decision‑making, and intelligent automation across the AI & HPC community. Success in this role requires strong cross‑campus collaboration with Technology Services, academic units, research teams, and external partners to deliver scalable, innovative solutions aligned with institutional goals. You’ll also play a key part in shaping policy, ensuring compliance, strengthening research partnerships, and representing Texas A&M HPRC at regional and national events as you help build a vibrant, forward‑looking ecosystem for AI and data‑intensive computing.

Requirements

  • 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.
  • Ability to occasionally work outside of normal working hours and weekends, may require some domestic travel.

Nice To Haves

  • A Ph.D. in 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.

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.
  • Provides 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.
  • Act as a visionary, 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.
  • Lead or participate in proposal development securing funding in AI and data-intensive computing related fields.
  • 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.
  • Supervises assigned staff.
  • Empower 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.

Benefits

  • Medical, prescription drug, dental, vision, life and AD&D, flexible spending accounts , and long-term disability insurance with Texas A&M contributing to employee health and basic life premiums
  • 12- 15 days of annual paid holidays
  • Up to eight hours of paid sick leave and at least eight hours of paid vacation each month
  • Automatic enrollment in the Teacher Retirement System of Texas
  • Free exercise programs and release time
  • All employees have access to free LinkedIn Learning training, webinars, and limited financial support to attend conferences, workshops, and more
  • Educational release time and tuition assistance for com p leting a degree while a Texas A&M employee
  • Living Well, a program at Texas A&M that has been built by employees, for employees
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