Director, AI and Intelligent Automation

At GAF, we cover more than buildings. We cover each other. No matter what role, tenure, or track, under this roof you are empowered to be there for your teammates, your customers, and especially your community. Under this roof, we don’t back down from hard work– we support one another in pursuit of something bigger. We define the future while leading the present. And under this roof, we own our opportunities. Becoming the market leader only happens when everyone feels they have the opportunity, and the support, to thrive. We are GAF. And under this roof, we protect what matters most.

Job Summary The Director of AI and Intelligent Automation is a critical leadership role responsible for architecting and executing the enterprise-wide AI journey. Reporting directly to the VP of Data and AI, this individual will own the AI execution strategy, business alignment, and portfolio prioritization and delivery approach for the entire organization in partnership with different departments. The primary objective or the role is to transform the company to use AI technology to be more effective and efficient in delivering the business strategies - from individual productivity aids to robust, automated enterprise solutions that drive systemic efficiency and measurable financial returns.

Essential Duties

• Vision and Execution Strategy

  • Define and own the execution strategy for the enterprise AI roadmap, ensuring alignment with the overarching vision to position AI as a “Technology Multiplier” for people and processes.

  • Facilitate alignments and deliverables on AI automation across all business functions

  • Manage the full innovation lifecycle: from initial “Culture Core” engagement to scaled “Enterprise Deployment” of custom Agentic workflows.

• Solution Design & Engineering Oversight

  • Oversee the development and deployment of Generative & Agentic AI solutions, including custom RAG (Retrieval-Augmented Generation) repositories and autonomous multi-agent workflows.

  • Guide the technical team in building robust Computational AI models, such as simulations for R&D, supply chain, and manufacturing optimizations.

  • Establish reusable technical patterns and platform controls to ensure scalable and reliable AI operations.

• AI Governance & Risk Management

  • Partner with Cyber Security, Legal, and Procurement to establish and enforce robust governance frameworks for responsible AI adoption.

  • Lead the evaluation of third-party AI solutions through comprehensive questionnaires to ensure compliance with enterprise security and data privacy standards.

  • Define success metrics and KPIs for AI implementations, monitoring performance, user adoption, and ROI.

  • Review AI use cases for viability and financial returns.

• Enablement & Change Management

  • Co-Launch and co-lead the Data and AI Academy to provide role-based, tiered education on AI practices and tools for the entire workforce.

  • Democratize innovation by managing the “Idea Collection Engine,” systematically capturing and evaluating high-ROI pain points directly from employees.

  • Act as the critical bridge between technical engineering teams and non-technical business stakeholders.

Qualifications Required

• Bachelor’s Degree is required
• 10 + years relevant experience

• Technical Expertise

• Advanced AI Literacy: Deep conceptual and practical understanding of LLMs, Retrieval-Augmented Generation (RAG), and agentic orchestration frameworks.

• Programming & Frameworks: Proficiency and experience with orchestration tools such as LangChain, LlamaIndex, or AutoGen.

• Architectural Knowledge: Familiarity with vector search and storage solutions (e.g., Vertex AI Search) and API integration strategies.

• Leadership & Strategy Architectural Knowledge: Familiarity with vector search and storage solutions (e.g., Vertex AI Search) and API integration strategies.

• Lead: Effectively lead a team of AI process engineers and builders including the ability to define and manage budgets and demand vs capacity. Influence thought leadership and work across all functions to drive and enable AI use cases.

• Business Analysis: Exceptional ability to map complex business processes and identify viable candidates for AI integration.

• Agile Methodology: Experience managing project backlogs, writing robust technical documentation, and leading cross-functional …