Principal Program Manager - Generative AI Implementation (100% Remote)

Allshore Talent•Ambinany, B

9d•Remote

About The Position

The Principal Program Manager leads complex enterprise generative AI implementation programs from planning through deployment, adoption, and ongoing optimization. The role aligns technical implementation, business objectives, governance, organizational readiness, and user adoption, and establishes the operating structure needed to deliver measurable results. It requires leading large-scale enterprise software implementations, driving accountability across teams, navigating technical and organizational complexity, and communicating effectively with senior executives. The successful candidate combines strong program-management discipline with an understanding of generative AI, enterprise technology, data, security, governance, and organizational change. The role ensures that AI capabilities are operationalized and adopted, with sustainable governance and operating models, rather than merely deployed.

Requirements

Ten or more years of progressive program or project management experience.
At least five years of experience managing complex enterprise software, technology, platform, or digital transformation implementations.
Demonstrated experience leading large, multi-workstream programs involving business, technology, data, security, governance, and organizational change.
Strong understanding of artificial intelligence and machine-learning technologies, particularly generative AI applications in enterprise environments.
Experience managing implementation, integration, adoption, or scaling of AI-enabled products or capabilities.
Ability to navigate complex technical architectures, system integrations, data ecosystems, and implementation dependencies.
Understanding of enterprise data quality, security, privacy, governance, performance, responsible AI, and production-readiness considerations.
Experience developing and executing organizational change-management and adoption plans.
Experience establishing program governance, success metrics, reporting, delivery methodologies, documentation standards, and stage gates.
Experience leading programs using Scrum@Scale, SAFe, Disciplined Agile, LeSS, or a comparable scaled delivery framework.
Demonstrated ability to manage concurrent workstreams and proactively resolve cross-team dependencies.
Experience facilitating steering committees, governance reviews, executive business reviews, and cross-functional program meetings.
Strong executive presence and ability to communicate technical progress, risks, decisions, and tradeoffs to non-technical leaders.
Demonstrated ability to influence teams and stakeholders without direct authority.
Strong accountability, urgency, organization, and ownership.
Excellent written, verbal, facilitation, and stakeholder-management skills.

Nice To Haves

Experience leading enterprise generative AI or agentic AI implementations.
Experience taking an AI capability from proof of concept through production deployment and enterprise adoption.
Consulting or professional services experience working directly with large enterprise clients.
Experience within Adobe, digital experience, creative production, content supply chain, MarTech, or enterprise workflow environments.
Experience coordinating globally distributed teams and delivery partners.
Experience managing vendor, platform, and systems-integration dependencies.
Knowledge of AI governance, responsible AI, model evaluation, human-in-the-loop workflows, and production AI operations.
Relevant program-management or Agile certifications.

Responsibilities

Lead large-scale enterprise generative AI implementation programs from planning through deployment, adoption, and ongoing optimization.
Translate business objectives and technical requirements into an integrated implementation strategy, program roadmap, and measurable delivery plan.
Develop adoption plans addressing organizational change, communications, training, skill development, process redesign, and user readiness.
Establish governance models, decision-making structures, success metrics, and scalable roadmaps for embedding generative AI capabilities in client organizations.
Keep implementation decisions aligned with business outcomes, technical feasibility, security requirements, governance standards, and responsible AI practices.
Partner with business, technology, data, security, legal, compliance, and change-management leaders to resolve issues and maintain alignment.
Help clients progress from experimentation and isolated use cases to scalable, repeatable, and governed enterprise AI capabilities.
Lead cross-functional teams of consultants, engineers, architects, data professionals, change-management leaders, and subject matter experts.
Manage multiple concurrent workstreams, including integration points, dependencies, milestones, risks, and decisions.
Establish program structure, execution methodology, documentation standards, controls, and stage gates for predictable delivery.
Develop and maintain integrated program plans covering scope, schedule, resources, dependencies, milestones, risks, decisions, and business outcomes.
Drive accountability by assigning ownership, monitoring commitments, escalating obstacles, and ensuring timely resolution.
Create and operationalize risk-mitigation strategies for technical, organizational, data, security, governance, adoption, and delivery challenges.
Ensure required documentation, approvals, quality controls, and governance checkpoints are completed.
Monitor program health and adjust plans in response to business needs, technical constraints, implementation findings, and adoption results.
Identify cross-program conflicts and influence peripheral teams to prioritize work required for successful delivery.
Maintain delivery discipline while adapting implementation approaches as client needs and technical capabilities evolve.
Establish and facilitate cross-functional and cross-program operating cadences.
Lead program syncs, workstream reviews, governance meetings, steering committee sessions, and executive business reviews.
Provide visibility into program progress, outcomes, risks, dependencies, decisions, and required leadership actions.
Create executive-level reporting that connects implementation progress to business value and adoption.
Facilitate decisions and tradeoff discussions involving scope, timing, risk, resources, technical complexity, and organizational readiness.
Keep business and technical stakeholders aligned on priorities, responsibilities, decisions, and success criteria.
Communicate upcoming changes and their potential impacts on users, business processes, technical teams, and customers.
Define and report metrics covering delivery performance, implementation quality, risk, adoption, operational readiness, and business outcomes.
Partner with change-management and business leaders to identify impacted roles, processes, skills, and operating models.
Develop adoption strategies addressing stakeholder engagement, communications, training, enablement, feedback, and reinforcement.
Track adoption and usage metrics, identify barriers, and implement corrective actions.
Establish feedback loops so implementation and adoption strategies can evolve based on user needs and program results.
Support sustainable governance and operating models that remain effective after implementation.