Executive Director of Applied AI

Define and lead the applied AI deployment strategy, execution roadmap and business integration model across enterprise business units. Act as a forward-deployed AI engineering leader, partnering directly with business teams to translate strategic priorities into deployable products, intelligent workflows and redesigned processes. Lead technical solution architecture for complex AI deployments, making hands-on decisions on application architecture, system integration patterns, model orchestration, APIs, security controls and production infrastructure. Lead end-to-end implementation, customization, integration and scaling of generative AI, agentic systems and workflow automation solutions in production environments. Build, lead and coach a small, globally distributed team of forward deployed AI engineers, establishing engineering excellence through technical review processes, coding standards and career development while actively guiding delivery on critical engagements. Establish delivery frameworks and engineering standards that support scalability, reliability, security, maintainability and sustained operational adoption. Create reusable AI services, accelerators, evaluation frameworks, blueprints and integration patterns that reduce time to value across business domains. Partner with data, infrastructure, information security, architecture, compliance and business teams to align solutions with enterprise priorities and regulated-environment requirements. Track solution performance, adoption and business value through monitoring, feedback loops, user analysis and continuous service optimization. Guide modernization of existing systems and processes so they can integrate with agentic AI products, applied AI models and enterprise technology platforms. Communicate business impact, technical transformation vision, delivery progress, risks and investment needs to senior executives and key stakeholders.

Novartis is making a significant long-term investment in becoming an AI-first organization, with sponsorship at the highest levels of the company. This is a rare opportunity to shape how generative AI and agentic systems are engineered, deployed and adopted across a global enterprise whose work ultimately supports patients and healthcare systems worldwide.

• Bachelor's degree in computer science, engineering, data science or a related field.

• At least 15 years of progressive experience in technology leadership, enterprise AI transformation or complex solution delivery, including leadership of senior technical and cross-functional teams.

• Deep, hands-on expertise in applied AI delivery, including taking machine learning, generative AI and agentic solutions from concept through production and enterprise-scale adoption.

• Strong software and product engineering grounding, with experience integrating AI into complex enterprise platforms, data environments and operational workflows.

• Hands-on proficiency with modern AI engineering stacks, including Python, cloud platforms (e.g., AWS), LLM orchestration frameworks, vector databases, MLOps/LLMOps and software delivery practices.

• Demonstrated success defining and scaling enterprise-level AI initiatives, with measurable business value, automation or performance outcomes.

• Experience leading forward deployed, solutions engineering or technical consulting teams, translating ambiguous business problems into production-grade software systems in enterprise environments.

• Consulting or professional-services experience partnering with senior technology and business leaders on enterprise transformation, operating models or technology strategy.

• Proven people leadership and organizational development capability, including building high-performing teams, developing leaders and establishing effective governance.

• Strong executive communication and cross-functional influence skills, with the ability to align priorities, investment decisions and delivery across a complex matrixed organization.