Director, AI and Agentic Engineering

SUMMARY/JOB PURPOSE The Director, Engineering AI and Agentic leads the strategy, architecture, delivery, and operations of enterprise AI platforms and AI-enabled business solutions. This role combines deep AI engineering leadership with strong product management capabilities to translate business needs into scalable, secure, measurable, and user-centered AI products. The Director, Engineering AI And Agentic is accountable for building reusable AI platform capabilities, delivering production-grade agentic and generative AI solutions, advancing AI-native engineering practices, and partnering across IT, security, data, legal, compliance, and business stakeholders to responsibly scale AI adoption across Exelixis. ESSENTIAL DUTIES/RESPONSIBILITIES Define and execute the AI engineering strategy, roadmap, and operating model for enterprise AI platforms, reusable services, and AI-enabled business solutions. Lead the design and delivery of scalable AI platform capabilities, including model access patterns, agent orchestration, retrieval-augmented generation, evaluation frameworks, prompt and artifact management, observability, governance controls, and reusable integration patterns. Oversee end-to-end development of production-grade generative AI, agentic AI, and automation solutions that improve productivity, decision support, operational efficiency, and business outcomes across functions. Apply strong product management practices, including opportunity assessment, stakeholder discovery, prioritization, roadmap planning, user experience definition, value measurement, adoption planning, and lifecycle management. Partner with business leaders, product managers, architects, data teams, cybersecurity, privacy, legal, compliance, and enterprise application teams to translate strategic business needs into secure, governed, and scalable AI solutions. Establish AI-native engineering standards and practices, including specification-driven development, agent-assisted software delivery, automated testing, code quality, reusable patterns, DevSecOps, CI/CD, release management, and operational support models. Ensure AI solutions are designed for reliability, security, scalability, auditability, explainability, human oversight, measurable autonomy, and responsible AI use consistent with company policies and regulatory expectations. Manage platform, and technology decisions across AI providers, cloud services, data platforms, development tools, and open-source components; assess build-versus-buy options and total cost of ownership. Create and monitor success metrics for AI platforms and solutions, including adoption, productivity impact, quality, latency, cost, risk reduction, reuse, user satisfaction, and business value realization. Lead architecture reviews, prompt and solution reviews, security reviews, model and agent evaluations, release-readiness assessments, and post-production performance monitoring. Develop talent, delivery practices, technical documentation, playbooks, reference architectures, and enablement materials that help teams adopt AI-native engineering safely and effectively. Performs other duties as assigned Complies with all policies and standards SUPERVISORY RESPONSIBILITIES Recruit staff to meet the unit’s immediate objectives and develop staff to meet longer term objectives. Appraise the performance of subordinates and recommend changes regarding job, pay and employment status. Assist with operating budgets, and capital budgets if required, and control expenses to adhere to approved budgets. Keep informed of company policies and procedures as well as keep current with technical and regulatory developments to ensure compliance. Develop policies and procedures or recommend revisions to facilitate the accomplishment of the unit’s objectives. Cooperate with management and staff of other organizational units to accomplish overall organizational objectives. Provide a safe workplace and ensure employees are aware of and adhere to