The Director of AI & Data Platforms is responsible for leading the enterprise strategy, architecture, engineering, and operations of TRS's artificial intelligence and data platforms. The incumbent will own the shared AI and data foundations that enable scalable, secure, and compliant analytics and AI capabilities across the organization, and ensure that platform capabilities, governance enforcement, and architecture standards are consistently applied to support business-driven data delivery and AI initiatives. This role is a key member of IT leadership and serves as the enterprise point of accountability for AI and data platform execution.
WHAT WILL YOU DO:
Leadership
- 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.
Enterprise Enablement & Adoption
- 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.
Enterprise AI & Data Platform Strategy, Architecture, and Governance
- 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 (FinOps).
- 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.
Platform Engineering, Operations, and Enablement
- Leads platform operations including monitoring, incident management, and reliability.
- Owns environment strategy (sandbox, development, testing, production).
- Establishes DevOps 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.