Manager, AI Excellence

Siemens•Wendell, NC

13h•$145,156 - $248,839•Onsite

About The Position

The Manager, AI Excellence leads the Business Unit’s Artificial Intelligence capability and is responsible for translating business strategy and opportunities into a focused portfolio of AI initiatives that deliver measurable value. This role serves as a player-coach, combining leadership of the AI Excellence team with hands-on involvement in AI initiatives, technology decisions, solution development, stakeholder engagement, and delivery. The Manager establishes the Business Unit’s AI vision and operating model while creating alignment between business stakeholders, Enterprise IT, central AI organizations, technology providers, and external partners. The role owns the overall AI portfolio and ensures that initiatives move effectively from opportunity identification through implementation, adoption, and value realization. Success requires someone who can operate comfortably between business strategy, technology, architecture, product management, and execution while establishing direction and helping solve complex problems.

Requirements

Bachelor’s degree required.
8+ years of experience with digital transformation, artificial intelligence, technology, product management, architecture, or related disciplines.
8+ years of experience leading complex technology initiatives across organizational boundaries, including business functions, IT organizations, and external partners.
8+ years of experience with Generative AI, AI platforms, agents, enterprise integration, data, and modern technology architectures.
8+ years of experience translating business problems into technical solutions and measurable business outcomes.
8+ years of experience in portfolio, program, stakeholder, vendor, and implementation partner management.
Legally authorized to work in the United States on a continual and permanent basis without company sponsorship.

Nice To Haves

Experience establishing an AI vision, operating model, roadmap, governance approach, or capability model within a business unit or enterprise environment.
Experience with enterprise architecture, data governance, cybersecurity, privacy, legal, intellectual property, or Responsible AI considerations.
Experience managing strategic relationships with third-party AI vendors, technology providers, implementation partners, or enterprise platform teams.
Experience leading small teams, developing capability owners, or building communities of practice such as AI champions, business subject matter experts, or technical communities.
Strong communication skills with experience engaging senior leadership, technical delivery teams, business stakeholders, and cross-functional partners.

Responsibilities

Defining and maintaining the Business Unit’s AI strategy, roadmap, capability priorities, and transparent portfolio of AI initiatives aligned to business value, feasibility, cost, risk, and organizational readiness.
Translating business strategy and operational challenges into actionable AI opportunities with measurable objectives, clear investment priorities, adoption plans, and value realization outcomes.
Leading high-priority AI initiatives from concept through architecture, development, deployment, adoption, and continuous improvement while removing organizational and technical barriers.
Providing technology and architecture direction for enterprise-approved and emerging AI solutions, including generative AI, AI platforms, agents, enterprise integration, data, cybersecurity, and scalable implementation approaches.
Partnering across business functions, Enterprise IT, central AI teams, data organizations, technology providers, and external partners to align priorities, mobilize resources, and deliver outcomes.
Ensuring AI initiatives incorporate cybersecurity, privacy, legal, data governance, intellectual property, and Responsible AI requirements without slowing practical experimentation and delivery.
Leading and developing the AI Excellence team and AI Champion community while building a culture focused on experimentation, pragmatism, measurable value, reuse, and responsible implementation.