HR AI & Digital Transformation Strategy Lead

Job Title:

HR AI & Digital Transformation Strategy Lead Job Category:
Information Technology Time Type:
Full time Minimum Clearance Required to Start:
None Employee Type:
Regular Percentage of

Travel Required:

Type of Travel:*
* * The Opportunity The HR AI & Digital Transformation Strategy lead is responsible for shaping and executing the enterprise HR AI strategy, owning the HR data architecture, and guiding the evolution of intelligent, data‑driven HR capabilities. This role leads AI initiatives across the HR ecosystem, ensuring readiness, governance, and scalability of HR data to power analytics, automation, and next‑generation workforce technologies.

Serving as the HR data architecture owner, the HR AI & Digital Transformation Strategy lead ensures that data foundations, models, and tools are designed for secure, compliant, and efficient AI‑enabled services. The ideal candidate brings deep technical expertise, strong business acumen, and exceptional communication skills, excelling at cross‑functional influence to drive alignment and adoption across CACI.Responsibilities:

AI & Digital Transformation Operationalize the AI in HR strategy, serving as owner of the HR data layer powering AI‑enabled tools, automated processes, and workforce insights.

Assess data readiness for AI/ML models, including quality, completeness, governance alignment, and remediation needs.

Shape data strategies and architecture for AI pilots and long‑term initiatives, ensuring compliance with governance and emerging AI regulations.

Partner with IT, Legal, Finance, and vendor teams to evaluate AI vendor data practices and ensure responsible, secure use of HR data.

Stay current on evolving AI regulatory frameworks and embed compliance considerations into design and architecture decisions.

Strategy & Roadmap Build and maintain the multi‑year HR data and AI architecture roadmap aligned with HR priorities and enterprise technology strategy.

Advise HR leaders on data capabilities, limitations, risks, and prioritization opportunities.

Lead through influence, driving alignment and momentum across HR, IT and the business.

Serve as HR’s technical and strategic expert during AI platform evaluations, RFPs, and vendor assessments.

Translate complex AI, data, and architectural concepts into clear and compelling narratives for executive and non‑technical audiences.

HR Data Architecture & Governance Design, document, and maintain the end‑to‑end HR data architecture across the HR technology ecosystem.

Define and enforce data standards, taxonomies, and governance practices to ensure accuracy, consistency, and compliance across HR data domains.

Lead development and maintenance of data dictionaries, lineage documentation, and conceptual/logical/physical data models.

Partner closely with enterprise data governance teams to ensure HR data aligns with organization‑wide policies and frameworks.

Identify and remediate data quality issues, redundancies, and structural debt across HR systems and integrations.

Continuously refine data models to support scalable reporting, analytics, and AI/ML consumption.

Analytics & Reporting Enablement Establish and maintain the data infrastructure needed for workforce analytics, dashboards, and HR reporting.

Partner with analytics and BI teams to ensure data availability, consistency, performance, and fitness for downstream use.

Define and manage data pipelines, ingestion patterns, and integration requirements supporting workforce reporting and AI‑driven insights.

Enable self‑service analytics by ensuring HR data assets are well‑structured, governed, and documented for broad consumption.

Qualifications:

Required:

10+ years of experience in data strategy, analytics and/or architecture, with meaningful exposure to human resources

Familiarity with HR technology ecosystems with working knowledge of platforms such as Workday, major ATS/TMS vendors, Talent Intelligence, LMS platforms, and HR analytics tools

Experience designing data infrastructure to support AI/ML use cases, including feature engineering, model input pipelines, and output activation

Strong command of data governance principles, including data quality management, metadata…