Job Description Summary:
The Director, Applied AI & Agentic Solutions is responsible for leading the delivery, adoption, and evolution of artificial intelligence engineering capabilities across a portfolio of digital products within the Global Digital Network. This role combines technical leadership, organizational leadership, and hands-on engineering expertise to enable product teams to build, deploy, and operate secure, scalable, and business-impacting AI solutions.
Reporting into the Senior Director, AI Engineering Lead, this role translates enterprise AI engineering strategy into delivery execution, reusable capabilities, and engineering practices across product teams. The Director leads AI engineers and technical specialists while partnering closely with Product, Data Science, Product Engineering, and Core Technology teams to ensure AI solutions achieve intended business outcomes and align with enterprise standards.
The successful candidate is a highly credible technical leader who can operate as a player-coach when needed, balancing strategic thinking with practical delivery execution. They are passionate about developing engineering talent, advancing AI engineering maturity, and helping product teams successfully adopt emerging AI technologies.
What You'll Do for Us
Lead the delivery and adoption of AI engineering capabilities across a portfolio of digital products, ensuring solutions are scalable, secure, resilient, and aligned to business priorities.
Manage and develop AI engineering teams, providing coaching, technical direction, performance leadership, and career development.
Partner with Product Managers, Technical Leads, Data Scientists, and Product Engineering leaders to prioritize and deliver high-value AI solutions.
Translate enterprise AI strategy, architecture standards, and platform capabilities into actionable delivery roadmaps and implementation plans.
Provide technical leadership on complex AI initiatives, including model architectures, agent workflows, retrieval strategies, evaluation approaches, and production deployment decisions.
Drive adoption of enterprise AI standards, reusable patterns, development tools, and engineering best practices across product teams.
Lead the design, development, deployment, and operation of production AI applications, LLM-powered products, and agent-based solutions.
Ensure effective implementation of MLOps, LLMOps, and AgentOps practices, including lifecycle management, deployment automation, observability, monitoring, and operational governance.
Establish engineering quality standards through architecture reviews, code reviews, testing practices, and operational readiness assessments.
Partner with Core Technology teams to leverage enterprise AI platforms, orchestration services, and foundational capabilities while identifying opportunities for enhancement.
Ensure AI solutions comply with enterprise governance, security, responsible AI, privacy, and risk management requirements.
Drive AI observability and operational excellence through monitoring, evaluation, performance optimization, and continuous improvement practices.
Support the delivery of enterprise digital twin, forecasting, simulation, optimization, and intelligent automation capabilities.
Evaluate emerging AI technologies and engineering approaches and recommend opportunities that improve delivery effectiveness and business impact.
Foster a culture of experimentation, learning, collaboration, and engineering excellence across AI engineering teams.
Requirements & Qualifications
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, Data Science, or a related technical discipline.
8+ years of experience in software engineering, AI engineering, machine learning engineering, platform engineering, or related technical disciplines.
5+ years of experience leading engineering teams, technical leads, or specialized engineering functions.
Demonstrated experience delivering production AI solutions, including generative AI, large language model applications, intelligent agents, and machine learning systems.
Experience leading delivery across multiple products or business domains in a matrixed environment.
Strong expertise in agentic AI architectures, Retrieval-Augmented Generation (RAG), GraphRAG, semantic search, vector databases, knowledge graphs, and AI orchestration frameworks.
Hands-on technical expertise in Python and cloud-native application development, with Azure preferred.
Experience implementing and operating MLOps, LLMOps, and AgentOps capabilities in production environments.
Experience establishing engineering standards, reusable frameworks, development accelerators, and operational best practices.
Knowledge of responsible AI, cybersecurity, privacy requirements, model governance, and enterprise risk controls.
Strong leadership capabilities with experience coaching engineers, leading technical teams, and driving organizational capability growth.
Excellent communication, stakeholder management, and influencing skills.
Strong business acumen and demonstrated ability to connect technical solutions to measurable business outcomes.
Skills:
Agile Methodology, Application Development, Business Processes, Business Value Creation, Change Management, Influencing, Microsoft Azure, Microsoft Office, Negotiation, Process Improvement Plans, Risk Mitigation Strategies, Software Development, Software Development Life Cycle (SDLC), Strategic IT, Vendor Management, Waterfall ModelPay Range:
United States: 171,000 - 198,000 USDBase pay offered may vary depending on geography, job-related knowledge, skills, and experience. A full range of medical, financial, and/or other benefits, dependent on the position, is offered.
Annual Incentive Reference Value Percentage:
30Annual Incentive reference value is a market-based competitive value for your role. It falls in the middle of the range for your role, indicating performance at target.
Location(s):
United States of AmericaCity/Cities:
AtlantaTravel Required:
00% - 25%Relocation Provided:
YesJob Posting End Date:
September 18, 2026Our Purpose and Growth Culture:
We are taking deliberate action to nurture an inclusive culture that is grounded in our company purpose, to refresh the world and make a difference. We act with a growth mindset, take an expansive approach to what’s possible and believe in continuous learning to improve our business and ourselves. We focus on four key behaviors – curious, empowered, inclusive and agile – and value how we work as much as what we achieve. We believe that our culture is one of the reasons our company continues to thrive after 130+ years. Visit Our Purpose and Vision to learn more about these behaviors and how you can bring them to life in your next role at Coca-Cola.
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity and/or expression, status as a veteran, and basis of disability or any other federal, state or local protected class. When we collect your personal information as part of a job application or offer of employment, we do so in accordance with industry standards and best practices and in compliance with applicable privacy laws.Skills Required
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, Data Science, or a related technical discipline
- 8+ years of experience in software engineering, AI engineering, machine learning engineering, platform engineering, or related technical disciplines
- 5+ years of experience leading engineering teams, technical leads, or specialized engineering functions
- Experience delivering production AI solutions, including generative AI, large language model applications, intelligent agents, and machine learning systems
- Experience leading delivery across multiple products or business domains in a matrixed environment
- Expertise in agentic AI architectures, Retrieval-Augmented Generation, GraphRAG, semantic search, vector databases, knowledge graphs, and AI orchestration frameworks
- Hands-on technical expertise in Python and cloud-native application development
- Experience with Microsoft Azure
- Experience implementing and operating MLOps, LLMOps, and AgentOps capabilities in production environments
- Experience establishing engineering standards, reusable frameworks, development accelerators, and operational best practices
- Knowledge of responsible AI, cybersecurity, privacy requirements, model governance, and enterprise risk controls
- Experience coaching engineers, leading technical teams, and driving organizational capability growth
- Excellent communication, stakeholder management, and influencing skills
- Strong business acumen and ability to connect technical solutions to measurable business outcomes
The Coca-Cola Company Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about The Coca-Cola Company and has not been reviewed or approved by The Coca-Cola Company.
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Retirement Support — Retirement benefits are positioned as a standout, combining a 401(k) match with a company-funded cash-balance pension and an employee stock purchase plan match that together materially increase long-term package value.
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Healthcare Strength — Health coverage is described as broad and feature-rich, including national medical coverage plus specialized add-ons like virtual care, second opinions, oncology navigation, fertility support, and chronic-condition programs.
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Leave & Time Off Breadth — Time-off benefits are outlined with structured vacation accrual that increases with tenure and a holiday program that includes both set and floating days.
The Coca-Cola Company Insights
What We Do
The Coca-Cola Company (NYSE: KO) is a total beverage company, offering over 500 brands in more than 200 countries and territories. In addition to the company’s Coca-Cola brands, our portfolio includes some of the world’s most valuable beverage brands, such as AdeS soy-based beverages, Ayataka green tea, Dasani waters, Del Valle juices and nectars, Fanta, Georgia coffee, Gold Peak teas and coffees, Honest Tea, innocent smoothies and juices, Minute Maid juices, Powerade sports drinks, Simply juices, smartwater, Sprite, vitaminwater and ZICO coconut water.
