Head of Engineering, North America Operating Unit Product Organization

The Coca-Cola Company•Atlanta, GA

14d•Hybrid

About The Position

This is a People Leader role. The incumbent must be currently based in or willing to relocate to the Atlanta, GA area and work a hybrid work schedule. Travel: Up to 25% travel with an expectation to be in the office 3 days a week. The Head of Engineering is a senior technology leader accountable for engineering strategy and execution across the North America Operating Unit (NAOU), supporting Customer Experience, Service Experience, Sales, and transaction growth capabilities that enable a $19B+ revenue portfolio. This is a foundational leadership opportunity, a chance to build a modern product engineering organization from the ground up inside one of the most recognized consumer brands in the world, with a team already in motion and the mandate, resources, and executive support to do it right. This leader will direct a scaled engineering organization of 100+ full-time associates and contractors, operating within a modern Product Operating Model. The role carries regional accountability for the resilience, scalability, and performance of platforms and products that directly impact customer engagement, service delivery, commercial performance, and data-driven decision making across North America. The position requires a combination of deep technical authority, product orientation, and executive leadership presence. The Head of Engineering must operate seamlessly across architecture reviews, product discovery, and business executive level conversations translating engineering strategy into measurable business outcomes while ensuring technical decisions align with long-term enterprise value creation. This leader will establish engineering as a strategic business partner, building empowered, outcome-driven teams that deliver durable, scalable platforms and differentiated digital capabilities that accelerate growth, operational efficiency, and competitive advantage across the NAOU portfolio.

Requirements

Strong partnership experience with Product Management and Product Design in empowered team environments.
5+ years, proven experience leading engineering organizations operating within a Product Operating Model or equivalent modern product-centric environment.
5+ years experience leading engineering through organizational transformation and modernization.
10+ years demonstrated success building and scaling high-performing engineering teams.
15+ years of progressive engineering experience, including both leadership roles and hands-on time building scalable solutions.
Deep technical expertise in modern software architecture, distributed systems, and platform engineering.
Strong understanding of cloud architectures, scalability, resiliency, and operational excellence.
Ability to engage deeply with engineers on architecture, design, and technical tradeoffs.
Track record of delivering complex, enterprise-scale platforms and systems.
Exceptional ability to communicate complex technical topics clearly to senior executive and business stakeholders.
Proven ability to influence senior leadership and shape enterprise technology strategy.
Strong business acumen with ability to connect engineering investments to measurable business outcomes.
Ability to operate effectively across both technical and business leadership environments.
Leadership Strategic Alignment: Translate high-level business objectives into a scalable technical roadmap, including the ability to make the case for architectural decisions to the North America Executive Leadership team and CIO.
Architectural Stewardship: Balance build vs. buy trade-offs with rigor and a long-term view, ensuring systems are built for durability and speed.
Talent Builder: Attracts, develops, and retains elite engineering talent with a clear philosophy on what great looks like.
Bachelor’s degree in engineering, computer science, or a related field required; advanced degree preferred.
Equivalent combination of relevant education, training, and demonstrated professional experience will also be considered.

Nice To Haves

Demonstrated experience leading AI or machine learning enablement initiatives within enterprise product or platform environments, with measurable business impact.
Familiarity with modern AI/ML platforms, LLM integration patterns, and the architectural requirements for scalable, governed AI deployment.
Proven ability to drive workforce and process transformation in support of AI augmented decision making.

Responsibilities

Engineering Leadership & Organizational Excellence Lead and develop a high-performing engineering organization operating under the Product Operating Model, with clear accountability for product and platform outcomes.
Build empowered engineering teams capable of owning business problems and opportunities end to end, from discovery through delivery, operation, and continuous improvement.
Recruit, develop, and retain top engineering talent, creating a culture of technical excellence, accountability, and continuous learning.
Establish clear engineering standards, operating rhythms, and accountability frameworks aligned to business outcomes rather than project completion.
Product Partnership & Outcome Ownership Partner closely with Product Management and Product Design in a durable one team model to solve meaningful business problems.
Ensure engineering teams contribute actively to product discovery, technical feasibility, and innovation.
Own the culture and operating model of the engineering organization, ensuring teams are builders and problem solvers, not order takers.
Drive accountability for measurable outcomes including business impact, system reliability, performance, scalability, and customer experience.
Ensure engineering decisions are aligned with product strategy, enterprise architecture, and long-term business priorities.
Technical Strategy & Architecture Leadership Define and evolve the technical strategy, architecture, and engineering practices required to support scalable, resilient, and secure product platforms.
Provide hands-on architectural guidance and technical oversight for critical systems and platform investments.
Ensure engineering teams build systems designed for scale, operability, resiliency, and long-term sustainability.
Balance speed of delivery with technical excellence, operational stability, and long-term maintainability.
Executive Engagement & Strategic Influence Serve as a trusted technical advisor to senior business and technology leaders, translating complex technical concepts into clear business implications.
Communicate engineering strategy, risks, tradeoffs, and investment needs to executive stakeholders with clarity and credibility.
Influence enterprise technology direction, ensuring alignment between product engineering, enterprise architecture, and business strategy.
Participate in executive planning cycles, helping shape technology investment priorities and long-term strategy.
Operational Excellence & Engineering Effectiveness Establish engineering metrics focused on outcomes, including system reliability, deployment frequency, cycle time, and business impact.
Drive adoption of modern engineering practices including continuous delivery, automated testing, observability, and platform engineering.
Ensure operational stability, resilience, and scalability of critical systems and platforms.
Foster a culture of accountability, ownership, and continuous improvement.
AI Enablement Champion the adoption and integration of AI and machine learning capabilities across the NAOU product and platform portfolio, positioning AI as a core driver of business performance, decision quality, and operational efficiency.
Define and execute an AI enablement roadmap that progressively embeds intelligence into customer experience, service delivery, and internal business processes advancing the organization from AI-assisted workflows toward AI enabled decision making at scale.
Partner with Product Management, Data & Analytics, and business stakeholders to identify high-value AI use cases that drive measurable outcomes, including revenue growth, cost reduction, customer satisfaction, and workforce productivity.
Lead engineering teams in building the foundational data, platform, and integration infrastructure required to support responsible, scalable AI deployment across the NAOU portfolio.
Drive organizational readiness for AI-augmented work including workforce process redesign, human-in-the-loop governance frameworks, and change enablement — ensuring teams are equipped to operate effectively in an AI-enabled environment.
Establish standards and guardrails for responsible AI use, including model governance, bias mitigation, transparency, and compliance with enterprise and regulatory requirements.
Continuously evaluate the evolving AI and generative AI landscape, identifying emerging capabilities that can be rapidly applied to create competitive differentiation across the North America business