Senior Manager, AI Portfolio and Enablement

Motorola Solutions•Chicago, IL

10d•Hybrid

About The Position

The AI Center of Excellence (CoE) is chartered to drive self-service enablement and the upskilling of AI talent across the enterprise. It serves as a central hub to enable business functions to share best practices, promote cross-team learning, and is responsible for delivering high-value AI use cases that create efficiencies, and deliver insights to support critical decision-making across the organization. We are seeking a highly experienced and strategic AI Leader to manage the intake, development, and scaling of the enterprise AI use-case portfolio. This role is critical to translating the CoE's mission into tangible business value by ensuring all AI initiatives are aligned with the overall enterprise strategy, follow governance standards, and drive measurable performance improvements.

Requirements

7+ years of demonstrable experience managing and scaling an AI/ML portfolio at a high-growth, technically mature organization.
Deep understanding of the AI/ML lifecycle, from ideation and development (AI Learning & Development, AI Upskilling) to deployment (Prompt Engineering, Model Deployment & Monitoring) and governance (Data Science Platform & Security).
Experience in data storytelling, upskilling, defining & establishing enterprise KPIs , and setting usage thresholds.
Strong change management skills with the ability to manage high-impact organizational change.
Excellent collaboration and communication skills, with the ability to influence technical and non-technical stakeholders.
Familiarity with industry-leading MLOps platforms (e.g., Kubeflow, SageMaker, Azure ML) and their role in enabling the Model Development and Model Deployment & Monitoring capabilities.
Demonstrated ability to drive consensus and present complex technical information to C-suite and executive steering committees.
Bachelors degree with 12 years of technical experience AND 7+ years of demonstrable experience managing and scaling an AI/ML portfolio at a high-growth, technically mature organization AND 5+ years of directly managing a team
Legal authorization to work in the U.S. indefinitely is required.
Employer work permit sponsorship is not available for this position.

Responsibilities

Portfolio Strategy & Development Manage the intake and qualification process for new AI requests, providing critical challenge to existing business leaders on feasibility, value alignment, and technical approach.
Design and implement the AI strategy roadmap, specifically defining the value realization model, associated KPIs, and calculations for enterprise use-case delivery.
Serve as the primary CoE liaison to platform teams, driving the technical requirements for integrating AI/ML models into existing platforms, tools, and architecture.
Collaborate with the business to shape and develop compelling AI use cases from ideation through deployment.
Establish and manage a robust use-case intake funnel, including initial scoring mechanisms to assess potential business value, technical feasibility, and alignment with the CoE's current Model Development roadmap.
Develop and maintain the enterprise-wide LLM (Large Language Model) usage policy, working with the Data Science Platform & Security team to ensure responsible scaling of generative AI capabilities.
Governance, Standards & Management Develop the core templates and data models for use-case reporting and performance metrics, establishing the single source of truth for AI value delivery.
Abide by and enforce policies and standards of data usage as defined by Governance and Operations teams.
Integrate AI and ML capabilities into standard reporting as needs arise, enabling the CoE to track and report on its value.
Manage the high level of change impact expected due to standing up non-existent capabilities and scaling existing ones across the organization.
Learning, Sharing & Enablement Champion and facilitate training and sharing of best practices across functions, including prompt engineering, model building, deployment, and monitoring practices/methodologies.
Lead AI communities that facilitate cross-team learning, knowledge sharing, and the creation of practice process creation and management.
Partner with HR, business teams, and functional teams to understand workforce and talent demands and support the creation of materials/assets to upskill & close talent/skill gaps.
Inter-Team Collaboration Provide guidance to Data Products & Platforms teams to build data infrastructure that enables core AI capabilities across the enterprise.
Evangelize policies and standards set by Governance & Operations across the enterprise.
Use the data products provided by the Data Team to derive business function needs that align with the Data Strategy.