Job OverviewThe
AI Delivery Manager is responsible for leading the end-to-end delivery of enterprise AI initiatives, ensuring that AI solutions are executed with discipline, governed responsibly, and delivering measurable business value. This role operates with
business strategy, data/AI engineering, and delivery execution, translating complex AI concepts into outcomes that matter to the organization.
The ideal candidate brings deep experience delivering complex technology initiatives, combined with a strong working understanding of AI, data, and automation. The AI Delivery Manager serves as the primary point of accountability for AI delivery outcomes-balancing speed, value realization, risk management, and adoption across multiple business domains.
A Day In The Life- Lead the end-to-end delivery lifecycle for AI initiatives, including intake, prioritization, delivery planning, execution, deployment, and post-production value tracking.
- Translate business needs into clear, actionable AI delivery plans, aligned with enterprise AI strategy and architecture standards.
- Own the AI use case backlog across agents and solutions, including backlog intake governance, sequencing logic, dependency management, and readiness criteria for what moves into delivery next.
- Lead structured discovery and working sessions with business stakeholders to finalize business requirements, document scope and acceptance criteria, and secure alignment and sign-off before build execution begins.
- Coordinate and lead cross-functional teams, including data scientists, ML engineers, platform teams, architects, security, and external vendors.
- Apply appropriate delivery methodologies (Agile, hybrid, product-centric) to ensure predictable and transparent execution.
- Define and continuously improve AI delivery standards for Hubbell, including the intake form, delivery playbook, stage gates, definition of done, and core governance checkpoints used across initiatives.
- Identify, communicate, and mitigate delivery risks unique to AI, including data readiness, model quality, integration complexity, security, and regulatory constraints.
- Define and track success metrics and value realization, such as ROI, productivity gains, accuracy, cycle-time reduction, or risk mitigation.
- Manage the blended delivery resource pool across internal team members and external partners, including consultants and strategic providers, to align capacity, skills, and assignments to priority AI initiatives.
What will help you thrive in this role?- Bachelor's degree in computer science, Information Technology, or a related field.
- 10+ years of experience in technology delivery, program management, product delivery, or digital transformation roles.
- Proven experience managing complex, cross-functional programs with multiple stakeholders and dependencies.
- Experience working in regulated or security-conscious environments is preferred.
- Strong understanding and working knowledge of:
- Machine learning and generative AI concepts
- Data pipelines, model lifecycles, and AI deployment patterns
- AI Platforms, cloud environments, and MLOps concepts
- Excellent stakeholder management and communication skills, including executive-level communication.
- Excellent analytical and problem-solving skills, with the ability to think strategically.
- Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at all levels of the organization.
The above summary of position responsibilities and requirements is not intended, and should not be construed, to be an exhaustive list of duties, skills, efforts, physical requirements, or working conditions associated with the position. It is intended to be an accurate reflection of those principal position elements essential for making decisions related to position performance, employee development, and compensation.
