Manager, AI Delivery

Hubbell Incorporated•Maryland Heights, MO

13d

About The Position

The 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.

Requirements

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.
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.

Nice To Haves

Experience working in regulated or security-conscious environments is preferred.

Responsibilities

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.