Senior Director, AI Engineering Lead

The Coca-Cola Company

. Define the enterprise AI engineering roadmap in partnership with Core Technology and Engineering teams .

Posted 10/23/2026full-timeAtlanta • United StatesSenior💰 $202,000 - $229,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI engineering leadership, including the development of AI architectures, end-to-end ML pipelines, and production AI systems. Proven ability to mentor teams, establish engineering best practices, and optimize AI solutions for enterprise-scale applications.

Highest-signal resume keywords

AI Engineering LeadershipEnd-to-End ML Pipeline DevelopmentProduction AI Systems DesignStrong Programming Skills in PythonExperience with MLOps Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI Architecture DevelopmentEnd-to-End ML Pipeline DesignPrompt EngineeringBackend EngineeringAPI and Service DesignCloud-Native Application DevelopmentModel Evaluation MethodsAI InteroperabilityTechnical MentorshipCode Review

Soft Skills

Excellent Communication SkillsStorytelling SkillsCoaching and Mentorship

Tools & Technologies

LangGraphLangChainSemantic KernelCrewAIOpenAIAnthropicAzure OpenAI

Certifications & Qualifications

BS or MS in Computer ScienceMachine LearningEngineering

Industry Keywords

AI Governance PracticesDigital Twin SolutionsAgent ArchitecturesRAGAI-Enabled Simulation Environments

Tech Stack

Tools & technologies

AzureCloudJavaPythonC++Go

About the role

Key responsibilities & impact

Define the enterprise AI engineering roadmap in partnership with Core Technology and Engineering teams
Build, lead, and develop a shared team of AI Engineers
Grow AI engineering capability through hiring, coaching, technical mentorship, and career development
Provide technical leadership on complex AI initiatives and contribute selectively to high-impact AI implementations
Partner with Tech Leads and engineering teams on model selection, prompt and agent architectures, retrieval and training pipelines, and evaluation strategies
Establish reference architectures and reusable engineering patterns for semantic layers, knowledge graphs, context engineering, RAG, GraphRAG, multi-agent systems, agent communication, tool orchestration, memory strategies, MCP, and A2A
Develop reusable SDKs, templates, CI/CD patterns, testing frameworks, and engineering accelerators
Define enterprise patterns for prompt lifecycle management, evaluation pipelines, observability, experimentation, cost optimization, deployment, and continuous improvement
Establish enterprise-wide telemetry, tracing, runtime monitoring, reasoning diagnostics, token analytics, dashboards, and evaluation frameworks
Improve model quality, latency, token efficiency, runtime cost, observability, and business outcomes through experimentation and optimization
Implement AI evaluation, guardrails, monitoring, access controls, audit logging, human-in-the-loop workflows, and secure agent execution
Establish AI architectures and reusable capabilities for enterprise digital twin solutions
Collaborate with Product, Data Science, Design, Core Technology, Product Managers, Product Owners, and Tech Leads
Promote AI engineering best practices, reusable components, tooling, and patterns across squads
Upskill engineers and continuously build organizational AI engineering capability

Requirements

What you’ll need

BS or MS in Computer Science, Machine Learning, Engineering, or a related technical discipline, or equivalent practical experience
8-10+ years of experience in software or AI/ML engineering
3+ years leading or managing engineering teams
Track record of shipping production systems that serve real users at scale
Experience designing, deploying, and operating production AI systems, including end-to-end ML pipelines, modern LLM-powered applications, and agentic AI solutions
Strong understanding of LLM-based systems, agent architectures, RAG, tool and function calling, prompt engineering, evaluation methods, and AI interoperability using MCP, A2A, or similar standards
Hands-on expertise in backend engineering, API and service design, and cloud-native application development
Strong programming skills in Python and one or more of Java, Go, or C++
Hands-on experience with LangGraph, LangChain, Semantic Kernel, CrewAI, or equivalent, and model providers such as OpenAI, Anthropic, or Azure OpenAI
Experience with MLOps, LLMOps, or AgentOps practices
Familiarity with enterprise AI governance practices, including model and prompt approvals, audit logging, data classification, risk controls, and responsible AI
Experience building AI capabilities for global, enterprise-scale products used across multiple markets
Experience supporting enterprise digital twin capabilities or AI-enabled simulation environments
Proven ability to establish AI engineering patterns, conduct code reviews, and develop engineers through coaching, mentorship, and hiring
Excellent communication and storytelling skills
Willingness to remain hands-on when tackling complex challenges
Must be currently authorized to work full-time in the United States and must not require The Coca-Cola Company's sponsorship

Benefits

Comp & perks

Annual incentive reference value of 30%
Medical, financial, and/or other benefits
Relocation provided
Travel required: 00% - 25%