AI Enablement & Engineering Manager

Trace3•Irvine, CA

1d•$142,727 - $150,000•Hybrid

About The Position

The Manager, AI Enablement & Engineering is responsible for driving enterprise adoption, operationalization, support, and value realization of AI tools and solutions across the organization. This role leads the enablement and operational engineering strategy for AI technologies including copilots, internal AI agents, workflow automations, enterprise AI productivity platforms, and emerging AI-enabled business solutions. This is a player-coach leadership role responsible for leading AI enablement engineers, analysts, automation specialists, and technical resources to deliver scalable AI adoption, automation, training, support, governance, and operational capabilities across the enterprise. The role partners closely with business stakeholders, IT leadership, Security, Infrastructure, Enterprise Applications, and AI engineering teams to ensure AI solutions are effectively deployed, governed, supported, adopted, and optimized for measurable business impact. The Manager, AI Enablement & Engineering combines technical leadership, operational management, user enablement, change leadership, and AI governance responsibilities to accelerate responsible AI adoption while improving employee productivity, operational efficiency, and business outcomes.

Requirements

Bachelor’s degree in Engineering, Computer Science, or related field (or equivalent experience) required.
Minimum of 5 years of experience in AI enablement, enterprise technology, digital transformation, automation, IT operations, or related roles.
Minimum of 3 years of leadership or technical program management experience.
Proven experience operating in a player-coach leadership role balancing strategic leadership with hands-on execution.
Experience leading technical teams supporting AI, automation, digital workplace, enterprise productivity, or SaaS platforms.
Hands-on experience implementing, configuring, supporting, or operationalizing AI-powered solutions such as copilots, AI agents, workflow automation tools, or generative AI platforms.
Experience partnering with AI engineers, developers, infrastructure teams, enterprise application teams, and business stakeholders.
Familiarity with enterprise AI ecosystems including Microsoft Copilot, OpenAI/ChatGPT Enterprise, automation platforms, knowledge management solutions, and AI productivity tools.
Experience using analytics, operational metrics, and reporting to measure adoption, usage, productivity impact, and value realization.
Understanding of AI governance, responsible AI practices, enterprise security, and compliance requirements.
Experience supporting APIs, integrations, workflow automation, or enterprise SaaS technologies.
Experience building enterprise training programs, operational support models, and enablement strategies.
Experience managing or partnering with enterprise software vendors and technology providers.
Experience supporting SaaS platform lifecycle management including licensing, renewals, adoption, and operational governance.
Familiarity with enterprise vendor management processes including security reviews, compliance considerations, and contract coordination.
Strong executive communication, presentation, and stakeholder management skills.
Ability to translate technical AI concepts into clear business and user guidance.
Strong analytical, organizational, and continuous improvement capabilities.

Responsibilities

Define and execute the enterprise AI enablement and operationalization strategy.
Develop programs to drive AI awareness, adoption, productivity, and measurable business value.
Partner with executive leadership to align AI initiatives with organizational priorities and transformation goals.
Establish success metrics, KPIs, and operational standards for AI adoption and value realization.
Drive enterprise AI best practices, governance alignment, and standardized usage guidance.
Lead AI enablement engineers and technical specialists responsible for deployment, configuration, integration, and operational support of enterprise AI solutions.
Oversee implementation and operationalization of AI copilots, internal AI agents, workflow automations, and AI-enabled productivity tools.
Partner with AI engineering, infrastructure, and enterprise application teams to prioritize integrations, enhancements, and AI platform capabilities.
Establish scalable operational processes, support models, technical standards, and documentation practices for AI-enabled services.
Support evaluation, pilot programs, and rollout of emerging AI technologies and platforms.
Ensure AI solutions align with enterprise architecture, security, governance, and compliance standards.
Drive operational maturity, scalability, and continuous optimization of enterprise AI services.
Collect and analyze user feedback, adoption trends, support metrics, and operational analytics.
Measure and report on AI adoption, productivity improvements, operational efficiencies, and business value realization.
Develop executive reporting and dashboards demonstrating ROI and impact of enterprise AI initiatives.
Identify gaps in usability, operational support, training effectiveness, or technical solution performance.
Partner with engineering and business stakeholders to improve AI capabilities using data-driven insights.
Drive continuous improvement initiatives focused on user experience, operational excellence, and AI effectiveness.
Oversee development and delivery of enterprise AI training programs, onboarding, and enablement resources.
Ensure effective education and support for tools including Microsoft Copilot, ChatGPT Enterprise, internal AI agents, automation platforms, and enterprise AI solutions.
Lead organizational change management initiatives to accelerate adoption and responsible AI usage.
Standardize enterprise AI usage guidance, playbooks, and best practices.
Promote AI literacy and responsible AI behaviors across business and IT organizations.
Own the enterprise AI support model and end-user experience strategy.
Manage AI support operations, ticketing processes, escalation workflows, and issue resolution coordination.
Identify recurring user issues and drive proactive operational or technical improvements.
Partner with engineering teams to troubleshoot and resolve complex AI platform issues.
Ensure a high-quality, scalable, and secure user experience for enterprise AI capabilities.
Partner with Security, Legal, Compliance, and IT leadership teams to enforce responsible AI governance standards.
Support governance processes for evaluating, approving, and operationalizing enterprise AI tools.
Ensure AI usage aligns with data protection, privacy, compliance, and acceptable use policies.
Promote secure and compliant usage of enterprise-approved AI technologies.
Assist in development and communication of enterprise AI policies, standards, and operational procedures.
Lead and develop a multidisciplinary AI Enablement & Engineering team including enablement engineers, automation specialists, business analysts, and support resources.
Establish team priorities, operational KPIs, delivery roadmaps, and service expectations.
Manage workload prioritization, resource planning, and execution of AI initiatives.
Provide technical and professional mentorship to team members supporting enterprise AI platforms and services.
Foster a culture of innovation, experimentation, accountability, and continuous learning.
Manage relationships with AI platform vendors, technology partners, and service providers.
Coordinate vendor onboarding, operational reviews, escalations, and ongoing platform governance.
Partner with Procurement, Security, Legal, and IT leadership on vendor evaluations, renewals, risk reviews, and licensing management.
Monitor vendor performance, platform adoption, support responsiveness, and roadmap alignment with business objectives.
Collaborate with vendors to identify optimization opportunities, feature enhancements, and best practices.
Support proof-of-concepts, pilot programs, and evaluation of emerging AI technologies and strategic partnerships.
Assist with forecasting, budgeting, and consumption management for enterprise AI platforms and services.