Senior Director, Data Science - AI Agent Development

About the Role The Senior Director of Data Science - AI Agent Development will lead the strategic and technical vision for Gap Inc.’s AI Agent ecosystem — a suite of generative and autonomous systems powering customer engagement, merchandising, and supply chain optimization. This leader will oversee a cross-functional organization of data scientists, machine learning engineers, and AI researchers, developing agentic systems that reason, plan, and act across the enterprise. You’ll work closely with senior executives, digital product, and technology teams to drive measurable business value through intelligent automation and human-AI collaboration. What You'll Do Strategic Leadership Define and execute the AI Agent strategy across Gap Inc.’s brands, aligning with enterprise digital transformation goals and customer experience objectives. Build and scale an AI Agent platform that supports customer service, digital styling, inventory intelligence, and creative design automation. ​ Technical and Organizational Leadership Lead a multidisciplinary team of data scientists, research engineers, and applied ML experts , focused on reinforcement learning, LLM orchestration, and multi-agent systems. Architect systems that combine retrieval-augmented generation (RAG), autonomous planning, tool use, and memory for scalable AI Agents across retail functions. Oversee Agent infrastructure, and experimentation frameworks to accelerate model deployment and iteration. Partner with product and platform engineering to ensure scalable APIs, model governance, and observability for AI Agents in production. Drive innovation and research partnerships with office of AI to stay at the frontier of agentic AI and generative reasoning. Partner with leadership to integrate AI-driven decisioning and co-pilot experiences across Enterprise and Product to Market. Establish frameworks for responsible and explainable AI , ensuring models align with brand values, diversity, and data privacy standards. Shape the long-term vision for human-AI collaboration , including associate enablement tools and in-store intelligence. ​ Operational Impact and Measurement Define and own key AI Agent performance metrics , including automation rate, customer engagement lift, and ROI on operational efficiency. Champion data-driven experimentation and A/B testing methodologies for AI-driven workflows. Create dashboards and narratives that translate AI impact into business outcomes for executive stakeholders. Who You Are Technical Expertise 10+ years of experience in applied data science, AI research, or machine learning engineering , including 5+ years leading large teams. Proven experience in LLM development, multi-agent systems, or intelligent automation (e.g., LangChain, OpenAI API, Anthropic, or custom orchestration frameworks). ​ Strategic and Leadership Skills Experience defining and executing AI strategy within a global consumer brand . Exceptional ability to translate technical complexity into clear business value narratives . Track record of building diverse, high-performing AI organizations . Deep commitment to ethical AI practices and customer trust. Strong collaborator with engineering, digital product, and marketing leadership. Strong understanding of deep learning, reinforcement learning, retrieval systems, and natural language processing . Hands-on knowledge of modern ML infrastructure (e.g., Databricks, AWS/GCP, Vertex AI, MLflow, Ray, Hugging Face). Expertise in data architecture, feature engineering, and experimentation pipelines at enterprise scale.