AI & Digital Innovation Delivery Director, Digital Transformation & Innovation

Managing Director, Ai & Digital Innovation Delivery

The Managing Director, AI & Digital Innovation Delivery is responsible for leading AI solution delivery strategy, engineering governance, and execution across the DT&I portfolio. This role provides oversight of multiple delivery functions, establishes enterprise-level standards, and ensures alignment with firm strategy, governance, and operational priorities. The Director collaborates with senior leadership to support the delivery of AI-enabled solutions and digital transformation initiatives.

• Develops and maintains AI solution delivery strategy aligned with firm priorities
• Establishes enterprise architecture standards for AI-enabled solutions
• Evaluates emerging technologies and determines applicability to the DT&I portfolio
• Supports development of reusable platforms and capabilities
• Provides oversight of multiple delivery teams and work streams
• Monitors delivery progress, risks, and outcomes
• Ensures alignment with timelines, budgets, and quality expectations
• Supports prioritization of initiatives and resource allocation
• Defines standards for SDLC processes, Dev Ops practices, and engineering quality
• Ensures consistency in deployment, testing, and release management practices
• Identifies risks related to scalability, performance, and technical debt
• Ensures alignment with firm governance, regulatory requirements, and security standards
• Supports implementation of AI governance and responsible AI practices
• Collaborates with risk and compliance stakeholders
• Communicates with senior stakeholders regarding delivery status and priorities
• Supports alignment between technology and business objectives
• Participates in governance and leadership forums
• Performs other duties as assigned
• Acts as a direct supervisor to team members and technical leads, as assigned
• Acts as a career advisor and mentor to team members as assigned

Education:

• Bachelor's degree required, focus in Information Systems, Computer Science, Engineering, Information Technology, preferred

Experience:

• Fifteen (15) or more years of experience in software development, AI/ML engineering, or cloud infrastructure, required
• Ten (10) or more years of experience as a lead developer writing production code, including AI/ML solution design and implementation, preferred
• Five (5) or more years of experience with AI orchestration frameworks (Semantic Kernel, Lang Chain, or equivalent) and Azure AI services, preferred
• Seven (7) or more years managing CI/CD pipelines and SDLC processes in Azure Dev Ops environments, preferred
• Experience establishing AI model governance frameworks including responsible AI policies and model lifecycle management, preferred
• Experience delivering enterprise-scale solutions in professional services, assurance, or accounting industries, preferred
• Experience with multi-agent systems, RAG architectures, and LLM function-calling patterns, preferred

License/

Certifications:

• N/A

Software:

• Extensive knowledge of Microsoft Azure including AI services (Azure AI Foundry, Azure OpenAI, Semantic Kernel) and application services (Azure Dev Ops, Azure Functions, Logic Apps, SQL Server), preferred
• Strong understanding of SDLC methodologies, Dev Ops practices, and CI/CD pipeline management, preferred
• Experience with AI orchestration frameworks (Semantic Kernel, Lang Chain, Auto Gen, Copilot Studio), preferred
• Extensive knowledge of prompt engineering, RAG patterns, vector databases, and embedding models, preferred
• Experience with BI tools (Power BI, DAX), CI/CD pipelines, and source control (Git), preferred
• Experience with containerization (Docker, Azure Container Apps) and monitoring tools (Azure Monitor, Application Insights), preferred

Language:

• N/A

Other Knowledge, Skills, & Abilities:

• Strong expertise in AI solution development, Dev Ops management, and designing scalable enterprise applications
• Ability to serve as a lead developer and AI architect while managing SDLC processes and providing team leadership
• Robust knowledge of AI agent patterns, Semantic Kernel architecture, prompt engineering, and model governance
• Familiarity with data architecture and ability to collaborate with data engineering and infrastructure teams
• Excellent problem-solving skills with a focus on AI safety, code quality, and operational reliability
• Strong communication skills with the ability to convey technical concepts to non-technical stakeholders and leadership
• Experience presenting AI solution and architectural recommendations to governance bodies (e.g., Architecture Review Boards)
• Strong knowledge of security best practices, responsible AI standards, and compliance considerations in enterprise environments
• Ability to work across technical teams and business stakeholders in complex, fast-paced enterprise environments
• Self-directed with the ability to manage multiple priorities and competing deadlines
• Collaborative mindset with the ability to build relationships across all levels of the organization

Individual salaries…