Director, AI Applications Engineering

ABOUT THE ROLE We are seeking a Director, AI Applications Engineering, to lead the design, development, and delivery of applied AI systems across business units. This role sits at the intersection of engineering leadership, AI/ML innovation, and product strategy. You will establish the vision for AI application engineering, build and mentor a cross-functional team, and ensure that our AI systems are production-grade, scalable, and aligned with business needs. This is both a strategic and hands-on role: you’ll partner with product and executive stakeholders to shape the roadmap, while guiding engineers through rapid prototyping, support of existing applications, and production delivery of AI-powered applications. WHAT YOU'LL DO As a Director, AI Applications Engineering on our team, you will own the: Strategy & Vision Define and own the strategy for AI applications across DPV, with emphasis on LLM and generative AI platforms. Shape and drive the enterprise-wide AI Applications strategy, ensuring consistency, scalability, and ethical best practices across business units. Establish and lead a Center of Excellence for Applied AI, creating reusable frameworks, standards, and accelerators that other teams can adopt. Partner with product and business leaders to identify high-value opportunities for AI application development. Guide build vs. buy decisions for applied AI systems, ensuring maximum value and IP ownership. Team Leadership Build, lead, and mentor a cross-functional team of AI/ML engineers. Foster a culture of innovation, technical depth, and pragmatic delivery. Guide technical and career development for engineers at all levels. Execution & Delivery Oversee design and delivery of AI-powered applications, such as conversational agents, agents, workflow automation, and recommendation systems. Ensure solutions are production-ready, scalable, and secure, with strong observability and testing practices. Drive adoption of modern GenAI practices: RAG pipelines, model fine-tuning, prompt/context engineering, evaluation frameworks, and guardrails. Stakeholder Engagement Serve as a key partner to executive stakeholders, communicating progress, risks, and outcomes clearly. Translate complex AI concepts into business impact narratives for leadership Act as a thought leader and evangelist for applied AI applications across the enterprise.