Senior Director, AI Engineering

About the role

The Sr. Director, AI Engineering at WCG is responsible for leading the design, development, deployment, and scaling of enterprise AI solutions across the organization. This role drives the implementation and operationalization of AI platforms, including machine learning, generative AI, and intelligent automation capabilities. This role balances strategic direction with hands-on execution oversight, ensuring AI solutions deliver measurable business value while meeting regulatory, quality, and operational standards.

Responsibilities

• Execute and operationalize the enterprise AI strategy, ensuring alignment to business priorities and measurable outcomes
• Drive design, adoption and growth of AI platforms (ML, GenAI, MLOps, LLMOps) across clinical, regulatory, and operational domains
• Lead prioritization of AI initiatives, balancing short-term delivery and long-term platform evolution
• Partner with executive stakeholders to translate business needs into scalable AI solutions
• Establish and scale enterprise-wide architectures for AI model development, deployment, monitoring, and lifecycle management
• Drive implementation and continuous improvement of AI platform infrastructure and pipelines
• Ensure AI platforms integrate seamlessly with enterprise data and technology ecosystems
• Establish and enforce Responsible AI frameworks including model validation, bias mitigation, explainability, and auditability
• Establish AI governance aligned with regulatory frameworks (GxP, ALCOA+, data integrity)
• Build, lead, and scale high-performing, globally distributed AI engineering teams
• Drive workforce planning, resource allocation, and capability building in AI engineering
• Collaborate cross-functionally with product, data, compliance, and IT teams
• Manage strategic vendor relationships and AI-related third-party platforms

Qualifications/Experience

• 10+ years of experience in AI/ML, data engineering, or advanced analytics
• 7+ years of leadership experience managing global engineering or AI teams
• Experience building and scaling AI and ML platforms in production environments
• Demonstrated ability to lead large-scale, cross-functional initiatives with measurable outcomes
• Deep knowledge of ML, NLP, and Generative AI technologies
• Experience using cloud platforms such as Azure, AWS, or GCP
• Experience managing vendors and distributed/offshore teams
• Familiarity with MLOps and LLMOps practices
• Experience working in regulated environments (strongly preferred)

Supervisory Responsibilities

Overall responsibility of management including direction, coordination, performance, and evaluation of the assigned team and staff. Responsibilities include training employees; planning, assigning, and directing work; appraising performance; rewarding and disciplining employees; addressing complaints and resolving problems.

Travel Requirements

10% to 20%