Sr. Director, Research Computing - Enterprise, Operations & Strategy

We need to output HTML fragment with sections: headings

for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections if posting has real specific content. We must not repeat job title as heading. Must not include Job ID etc. Remove boilerplate. Must preserve all substantive info. We need to parse the posting. First part: Position Information includes description of UT San Antonio, salary range (commensurate...), job type full time, posting close date, required application materials (resume, cover letter, references). We should drop application instructions? The instruction says remove application instructions. "Required Application Materials: Resume is requiredCover letter is required. Contact information for three professional references." That's application instructions; we should drop that. Also remove cookie/navigation/legal/EEO etc. The position info includes some descriptive text about university; that is substantive? It's about the instruction says preserve ALL substantive information; do NOT invent or summarize away detail. The description of university may be considered substantive? It's background about employer. Might be considered part of "About the role" or maybe we can include as a paragraph under "About the role". The heading "About the role" is allowed. We'll include that. Then Job Details: Job Summary (a paragraph). Then Core Responsibilities (a long list). Then Required Qualifications (list). Then Knowledge, Skills, And Abilities (list of keywords). Then Working Conditions (Office Environment...). We need to decide sections: About the role (maybe combine position information summary + job summary). Responsibilities (Core Responsibilities). Requirements (maybe Required Qualifications). Qualifications (maybe Knowledge, Skills, And Abilities). Skills (maybe also part of Knowledge, Skills, And Abilities). Benefits, Pay, Schedule: we have salary range: "Commencement with education, experience, and qualifications." That's vague; it's "Commensurate with education, experience, and qualifications." That's not specific; we should not create Pay section unless posting actually states them. It says salary range: Commensurate with education, experience, and qualifications. That's not a specific number or range; it's placeholder. According to rule: never emit a heading followed by filler/placeholder text (e.g., "commensurate with experience", "not specified", "N/A", "varies", "TBD") and never create Pay/Schedule/Benefits sections unless the posting actually states them. So we should NOT include Pay section. Benefits: none stated. Schedule: Full Time is stated; that's schedule info. Should we include Schedule section? The posting says Job Type: Full Time. That's a schedule. It's specific. So we can include Schedule section with "Full Time". However we need to check rule: "never create Pay/Schedule/Benefits sections unless the posting actually states them." It does state Job Type: Full Time. So we can include Schedule. But also we might include Benefits if any; none. We need to use

for section headings. Use

• for any list of duties/requirements/benefits, and

  for prose. We must not repeat the job title as a heading. The job title is "Senior Director for Research Computing". Not to be used as heading. We need to output only HTML fragment, no /, no markdown fences. Let's craft sections: - About the role: combine university description and job summary? Could be two paragraphs. We'll put

  About the role

  then

  with university description and job summary maybe combined. But we need to preserve all substantive info. The university description is long; we should keep it. The job summary also. We'll put them in separate

  under same section. - Responsibilities:

  Responsibilities

  then
  with each responsibility as
  • . Need to split the long list into items. The responsibilities are many sentences each starting with a verb. We'll break at each sentence that starts with a capital verb? We'll just split by periods that end a sentence and start a new responsibility. We'll need to ensure we keep all content. Let's extract responsibilities from the text after "Core Responsibilities". The text: "Develops and implements a multi-year research computing strategy aligned with institutional research priorities, partnering with research leadership, deans, and faculty to support sponsored research growth, faculty success, and emerging scientific and technology needs. Serves as the institution's principal voice on research computing, representing the integrated university to peer institutions, federal sponsors, the UT System, the Texas Advanced Computing Center, national laboratories, and technology partners. Serves as the institution’s principal advisor on artificial intelligence, leading enterprise AI strategy, governance, and adoption across research, clinical, educational, and administrative functions while advising leadership on opportunities, risks, and evolving regulatory requirements. Establishes and leads the institution’s AI governance framework, defining policies, standards, and oversight processes to ensure responsible, secure, and compliant AI adoption across the enterprise. Designs and manages a comprehensive research computing service portfolio, including HPC, AI/GPU, cloud, secure computing, data services, software support, training, and grant support, with clear service, allocation, and funding models. Establishes faculty engagement and research support programs that expand access to advanced computing services, support investigator success, and measure adoption, satisfaction, and research impact. Partners with principal investigators on grant proposals, contributing facilities and resources language, letters of support, cost share modeling, and infrastructure components for major funding opportunities including NIH S10, NSF CC*, NSF MRI, and DOD research instrumentation grants. Leads the architecture, procurement, deployment, and lifecycle management of institutional HPC and AI infrastructure, including CPU clusters, GPU systems for training and inference, high throughput and high bandwidth storage, scientific software environments, schedulers, and identity and allocation systems. Optimizes the mix of on premises infrastructure, commercial cloud, and external HPC access through the Texas Advanced Computing Center, ACCESS, and DOE leadership facilities to deliver the best price, performance, and time to science for each class of workload. Advances the institution’s AI research infrastructure, including GPU, model development, and MLOps capabilities, while partnering with faculty and research leaders to strengthen competitiveness for AI-focused research funding. Establishes standards, governance, and lifecycle management practices for responsible AI development and deployment, enabling secure, compliant, and scalable use of AI technologies across research and enterprise environments. Builds and manages secure research computing environments for regulated and sensitive data, ensuring compliance with applicable requirements and providing researchers with secure, audit-ready solutions throughout the data lifecycle. Establishes research data management services, including storage, archival, data sharing, metadata, and FAIR data practices, while supporting compliance with federal data management and sharing requirements. Develops and maintains research data governance policies for data classification, stewardship, retention, sharing, and provenance in partnership with research and compliance stakeholders. Establishes governance standards for AI training and evaluation data, including provenance, consent, quality, de-identification, and appropriate use. Partners with information security leadership to strengthen the security and compliance of research computing services, ensuring readiness for audits, certifications, and sponsor requirements. Builds the institutional capability to support classified or sensitive cleared research as the research portfolio grows in defense, intelligence, and homeland security domains. Ensures that research computing services are designed with security and compliance as embedded properties rather than after the fact additions. Leads the management of AI specific risk in partnership with the Chief Information Security Officer, privacy officers, and compliance leaders. Translates sponsor requirements into clear guidance, services, and controls that researchers can adopt without becoming compliance experts themselves. Develops a coherent hybrid infrastructure strategy that integrates on premises systems, commercial cloud services through enterprise agreements with AWS, Microsoft Azure, Google Cloud, and Oracle Cloud, and external HPC capacity through TACC, ACCESS, and partner institutions. Establishes institutional cloud landing zones for research that provide preconfigured network segmentation, identity integration, cost controls, security baselines, and data egress governance. Leads capital planning for research computing facilities, including data center capacity, power, cooling, networking, and physical security, and coordinate with facilities, real estate, and infrastructure partners to align research computing growth with institutional master planning. Makes research computing accessible to investigators and trainees at every career stage and from every discipline. Recruits, develops, and retains a research computing workforce and partners with academic departments to create joint appointments and internship pipelines. Advances AI literacy and enablement across the institution. Cultivates a service environment grounded in responsiveness, scientific curiosity, and genuine partnership with faculty. Owns the resilience strategy for research computing services, ensuring readiness to withstand, respond to, and recover from disruptions and major events. Leads resilience testing for research computing, including recovery exercises and failure simulations that validate readiness and response effectiveness. Drives continuous improvement in recovery time and recovery point objectives for critical research data and infrastructure, and gives research and IT leadership a clear view of resilience posture and remediation progress. Coordinates response and recovery during major incidents affecting research computing, including executive communication, prioritization, and restoration of service. Identifies and manages risks arising from research computing operations and strategic initiatives. Oversees resilience and risk requirements for critical third parties and vendors that support research computing, including cloud providers, external high performance computing partners, and scientific software suppliers, so that key dependencies do not become single points of failure. Advances execution discipline and program governance for research computing investments and capital programs, and drives organizational preparedness through training, awareness, and readiness exercises for research computing staff and the investigators they support. Operates the research computing function with disciplined financial management, sustainable funding models, and transparent business practices. Establishes service level commitments, performance metrics, and regular reporting to research and IT leadership. Uses metrics to inform investment decisions, retire underused services, and prioritize the work that produces the greatest scientific return. Maintains a forward looking technology roadmap that anticipates the next three to five years of scientific computing, AI, and data infrastructure needs, and presents that roadmap regularly to executive leadership and research stakeholders. Performs other duties as assigned." We'll make each sentence an
  • . Ensure we keep the content exactly. - Requirements: maybe we separate Required Qualifications and Knowledge, Skills, And Abilities into two sections: Requirements (maybe Required Qualifications) and Skills (Knowledge, Skills, And Abilities). The instruction says use headings like Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we can have:

    Requirements

    for Required Qualifications (list).

    Qualifications

    for Knowledge, Skills, And Abilities (list). Or maybe swap. But we need to follow typical: Requirements = mandatory qualifications; Qualifications = preferred? But we have only Required Qualifications and Knowledge, Skills, And Abilities (which are like competencies). We'll assign:

    Requirements

    for Required Qualifications (list).

    Skills

    for Knowledge, Skills, And Abilities (list). But the instruction includes Qualifications heading as possible. We could use both Requirements and Qualifications. Let's decide: Use Requirements for Required Qualifications (the bullet list). Use Qualifications for Knowledge, Skills, And Abilities (the list of competencies). That seems logical. Thus:

    Requirements

    with each qualification as
    • . The Required Qualifications text: "Bachelor's Degree in a related field. Ten (10) years of progressive experience in research computing, scientific computing, research informatics, or a closely related field, including a minimum of five years leading multidisciplinary technical teams that support faculty researchers. Demonstrated experience leading research computing environments, including HPC, GPU, AI, cloud, and hybrid infrastructure. Proven ability to support secure research operations involving regulated or controlled data, develop sustainable service delivery and funding models, and partner with researchers on sponsored grant proposals. Experience with operational resilience, disaster recovery, and critical infrastructure management. Knowledge of AI strategy, governance, risk management, and responsible AI practices in research, academic, or healthcare environments. This position may require the ability to maintain the security and integrity of UT San Antonio and its infrastructure per Texas EO-GA-48." We'll