Director, AI & Data Platforms

Director, AI & Data Platforms

Requisition

Employment Type:

Unclassified Regular Full-Time (URF)
Division:
Enterprise Data & Analytics
Compensation:
Depends on Qualification
Job Closing: 8/23/2026

Location:

TRS Headquarters Building 2 1900 Aldrich Street Austin, Texas, 78723 United States

The Information Technology (IT) Division lays the foundation for TRS to deliver excellent service experiences across the organization and with our members. We serve with purpose through mentorship and collaboration across a broad variety of teams unified by innovation to create technology and information solutions that have a positive impact on our members’ lives.

We invite you to join one of Austin’s Top Workplaces. TRS offers a best-in-class combination of technology and continuous learning opportunities to equip you to solve problems, expand your knowledge, and create impact for 1 in 20 Texans.

• Builds and leads a high-performing team of platform engineers, architects, AI engineers, and governance specialists.
• Develops workforce capabilities in AI and data platform engineering.
• Partners with IT leadership on organizational strategy and staffing growth.
• Directs department staff, directly and through team leaders, including hiring, directing, monitoring, evaluating, and motivating staff.
• Establishes clear career paths and role specialization within AI and data platform domains.
• Provides direction, monitors team work loads and work processes, and takes corrective actions as needed to ensure that all operations are covered, and productivity, customer service, and quality goals are met.
• Ensures compliance with applicable federal, state, agency, and department policies, procedures, rules, and regulations.
• Assesses training needs of team members and arranges for or provides training, coaching, and technical assistance.

• Serves as the enabling technology partner for Data Delivery and LOB teams.
• Provides “paved roads” for AI and data delivery teams.
• Supports developer experience, onboarding, and platform adoption.
• Reduces duplication and tool sprawl across the enterprise.
• Partners closely with Enterprise Technology Services to achieve enablement goals.

• Defines and execute the strategy for enterprise AI and data platforms (e.g., Fabric, Databricks, Azure AI services).
• Oversees platform architecture, engineering, and lifecycle management.
• Ensures scalability, reliability, performance, and cost optimization (Fin Ops).
• Establishes and maintains enterprise AI and data platform architecture standards.
• Ensures the platform provides the infrastructure and tooling to support AI-ready data patterns (e.g., semantic layers, RAG, data integration patterns).
• Drive consistency in interoperability and platform alignment.
• Owns platform architecture across the AI and data estate; sets architectural direction for how AI capabilities are built, deployed, and governed on shared infrastructure.
• Owns enterprise data governance tooling and enforcement mechanisms, including data catalog (Purview or equivalent), data classification and sensitivity labeling, access controls and policy enforcement.
• Ensure governance is implemented through platform capabilities, not manual processes.
• Partner with enterprise governance bodies to align policy with technical enforcement.

• Leads platform operations including monitoring, incident management, and reliability.
• Owns environment strategy (sandbox, development, testing, production).
• Establishes Dev Ops practices including CI/CD, version control, and deployment standards.
• Ensures secure, compliant, and auditable platform usage.
• Leads development of reusable AI capabilities (e.g., agents, copilots, orchestration frameworks).
• Supports AI experimentation, R&D, and transition to production-ready capabilities.
• Delivers shared services and patterns that enable downstream delivery teams.
• Performs related work as assigned.

• Bachelor’s degree from an accredited college or university in Computer Science, Information Systems, Engineering, or a closely related field.
• High school diploma or equivalent and additional full-time experience in data platforms, cloud architecture, IT enterprise or related experience may be substituted on an equivalent year-for-year basis.

• Eight (8) years of full-time directly related, progressively responsible experience in data platforms, cloud architecture, IT enterprise or related experience.
• Four (4) years of experience leading, or supervising the work of others, required.
• Experience with enterprise AI platforms and agentic frameworks (e.g., Azure AI Foundry, Azure OpenAI Service, Copilot Studio, Databricks Model Serving).
• Experience in enterprise AI adoption practices through agentic frameworks (Lang Chain, Semantic Kernel/Microsoft Agent Framework, Azure AI Agent Service), RAG pipeline design, MCP…