Director, Applied AI & Agentic Solutions
AI summary of the role
The Director, Applied AI & Agentic Solutions leads AI engineering delivery and adoption across a portfolio of digital products within Coca-Cola's Global Digital Network.
What you’ll do
- Lead delivery and adoption of AI engineering capabilities across a portfolio of digital products
- Manage and develop AI engineering teams, providing coaching and technical direction
- Partner with product, data science, and engineering leaders to prioritize high-value AI solutions
- Provide technical leadership on complex AI initiatives including agent workflows and production deployment
What you’ll bring
- 8+ years in software/AI/ML engineering or related disciplines
- 5+ years leading engineering teams or technical functions
- Experience delivering production AI solutions including generative AI and LLM applications
- Expertise in agentic AI architectures, RAG, GraphRAG, vector databases, and orchestration frameworks
Technologies
Python · Azure · LLM · RAG · GraphRAG · vector databases · knowledge graphs · MLOps · LLMOps · AgentOps · agentic AI · orchestration frameworks
About The Coca-Cola Company
Owns and markets ~200 beverage brands (Coca-Cola, Sprite, Fanta, Minute Maid) sold in 200+ countries, supplying concentrate to a worldwide bottling partner system.
Public · 5000+ people
Source and classification
Internal deployment & tooling · Evidence for this classification:
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
More from the 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, [... source excerpt omitted ...] 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 engineeri [... source excerpt omitted ...] tional 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 enginee
Employer postings · Data from · Sources