Director, Applied AI & Agentic Solutions

Coca-Cola; Georgia; On-site; USD 180,000 - 240,000; Full time

Job summary

Coca-Cola in Georgia, USA seeks a Director, Applied AI & Agentic Solutions to lead AI engineering across digital products, delivering scalable, secure AI solutions that drive business impact. You will coach AI engineers, partner with product, data science, and core tech teams, and translate AI strategy into actionable roadmaps and production deployments.

This role blends strategic leadership with hands-on delivery, advancing AI maturity and governance across enterprise platforms, ensuring

Qualifications

• Bachelor's or Master's degree in CS/AI/ML/SE/DS or related field.
• 8+ years in software/AI/ML/platform engineering roles.
• 5+ years leading engineering teams or technical leads.
• Proven production AI delivery including LLM apps and intelligent agents.
• Experience across multiple products in a matrix organization.
• Expertise in agentic AI architectures, RAG, semantic search, vector databases, knowledge graphs.
• Hands-on Python and cloud-native development; Azure preferred.
• Experience implementing MLOps, LLMOps, and AgentOps in production.
• Experience establishing standards, reusable frameworks, accelerators, and best practices.
• Knowledge of responsible AI, cybersecurity, privacy, governance.
• Strong leadership coaching engineers and leading technical teams.

Responsibilities

• 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 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 and foundational capabilities while identifying opportunities for enhancement.
• Ensure AI solutions comply with governance, security, responsible AI, privacy, and risk management requirements.
• Drive AI observability and operational excellence through monitoring, evaluation, and continuous improvement.

Skills

Leadership

Cross-functional collaboration

Strategic thinking

Mentoring/coaching

Education

Bachelor's/ Master's in CS/AI/ML/SE/DS

Tools

Python

Azure

MLOps

LLMOps

AgentOps

Knowledge graphs

Job description

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