Director AI-Enabled Engineering

MGM Resorts International•Las Vegas, NV

1d•Onsite

About The Position

The Director of AI-Enabled Engineering leads multiple engineering teams and drives the organization’s adoption of AI-augmented software delivery at scale. This role is responsible for shaping engineering strategy, optimizing organizational structure, and guiding technology investments and capability development to improve delivery effectiveness, quality, and innovation. Partnering closely with cross-functional leaders, the Director ensures alignment across product, design, and engineering while advancing consistent AI-enabled engineering practices across teams. The role oversees 2–5 engineering teams through Engineering Managers, with organizational responsibility for approximately 15–50+ engineers.

Requirements

3+ years of experience managing multiple engineering teams through Engineering Managers, with responsibility for organizational delivery, performance, and team development.
10+ years of professional engineering experience, including leadership across complex technical systems and large-scale software delivery organizations.
Demonstrated ability to lead multi-team engineering organizations, driving alignment, execution, and operational excellence across diverse teams and stakeholders.
Experience in AI-era workforce planning and organizational design, including adapting team structures, role composition, and capacity models to AI-augmented engineering environments.
Strong capability in defining technology strategy and making investment decisions aligned with product roadmaps, business priorities, and long-term organizational goals.
Fundamental understanding of “standards as code,” including the ability to encode engineering standards into AI-consumable and enforceable formats (e.g., ADRs, linting policies, machine-readable rules), while effectively managing the pace gap between rapidly evolving AI capabilities and business adoption.

Responsibilities

Own technical delivery, operational excellence, and engineering quality across a major product domain or platform area, ensuring scalable and reliable execution.
Define and drive technical strategy in alignment with product roadmaps, business objectives, and the organization’s long-term AI transformation goals.
Lead organizational and workforce planning decisions, including team structure, staffing levels, role composition, hiring priorities, and the balance between FTEs, contingent workers, and AI-enabled capacity.
Establish and scale engineering practices and standards across teams, including machine-readable “standards as code” frameworks such as ADRs, linting policies, and AI-enforceable development rules.
Partner closely with Product, Design, and Quality Engineering leadership to drive cross-functional strategy, execution alignment, and delivery effectiveness.
Advance AI-augmented engineering maturity by reassessing technical feasibility, optimizing the cost and sourcing model, and identifying opportunities where AI fundamentally changes delivery speed, capability, and organizational design.