Senior Manager, AI Engineer

The Coca-Cola Company

. Design, build, deploy, monitor, and optimize production-grade AI agents, GenAI solutions, and models .

Posted 10/14/2026full-timeAtlanta • United StatesSenior💰 $152,000 - $178,300 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing, building, and deploying AI agents and solutions, with a strong focus on Python programming, MLOps practices, and integrating AI capabilities into enterprise systems. Proficient in implementing AI safety controls and observability while collaborating effectively in agile environments.

Highest-signal resume keywords

Python ProgrammingMLOps PracticesAI Safety ControlsAzure Cloud InfrastructureAgile Delivery Environments

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Hard Skills

AI EngineeringMachine Learning EngineeringRESTful API DevelopmentVector DatabasesSemantic SearchModel DeploymentTesting and Version ControlDockerKubernetesData Privacy

Soft Skills

Analytical SkillsProblem-Solving SkillsCommunication Skills

Tools & Technologies

LangChainLangGraphCrewAISemantic KernelMCPA2AAzure MLOpsLLMOpsAgentOpsGraphRAG

Industry Keywords

Generative AIAI ObservabilityTelemetryEnterprise ApplicationsAgile Squads

Tech Stack

Tools & technologies

AWSAzureCloudDockerGoogle Cloud PlatformJavaKubernetesPythonC++

About the role

Key responsibilities & impact

Design, build, deploy, monitor, and optimize production-grade AI agents, GenAI solutions, and models
Connect agents to enterprise data, tools, and external systems using MCP and A2A standards
Write high-quality, tested, maintainable Python and other production AI code
Build and maintain Azure MLOps pipelines for training, versioning, inference, and CI/CD
Integrate AI capabilities into enterprise platforms, APIs, workflows, and user-facing features
Implement runtime observability and telemetry for AI agents and LLM applications
Build evaluation frameworks, harnesses, benchmark datasets, regression tests, and automated quality scoring
Design retrieval pipelines using semantic layers, knowledge graphs, vector search, and business ontologies
Configure AI safety controls, guardrails, human-in-the-loop workflows, autonomy thresholds, prompt injection defenses, and secure tool execution
Design and orchestrate multi-agent systems for enterprise workflows
Manage prompt versioning, experimentation, routing, cost optimization, and production lifecycle using LLMOps and AgentOps
Develop AI capabilities supporting enterprise digital twins
Collaborate with Technical Leads, software engineers, data engineers, and AI Engineers in agile squads
Contribute to sprint planning, backlog refinement, technical design discussions, code reviews, knowledge sharing, and engineering best practices
Stay current with AI, machine learning, and Generative AI advances and validate AI reliability, accuracy, and explainability

Requirements

What you’ll need

Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, Software Engineering, or a related technical field
3 to 5+ years of hands-on experience in AI or ML engineering, taking AI models and solutions from development to production
Strong proficiency in Python; working knowledge of Java or C++
Experience building and deploying LLM-powered and agentic AI applications using LangChain, LangGraph, CrewAI, Semantic Kernel, MCP, A2A, or similar
Experience deploying and operating AI/ML solutions on cloud infrastructure; Azure strongly preferred, AWS or GCP acceptable
Experience with vector databases, embeddings, RAG, GraphRAG, semantic search, or context engineering
Experience developing RESTful APIs or integrating AI capabilities into enterprise applications
Experience with MLOps, LLMOps, or AgentOps practices
Strong software engineering fundamentals, including API design, testing, version control, CI/CD, Docker, Kubernetes, model deployment, and monitoring
Experience in Agile delivery environments, including sprint execution, code reviews, and cross-squad collaboration
Experience implementing responsible AI practices, runtime guardrails, AI safety controls, explainability, data privacy, and secure agent execution
Experience implementing AI observability and telemetry
Strong analytical and problem-solving skills
Excellent communication skills
Must be currently authorized to work full-time in the United States and must not require company sponsorship

Benefits

Comp & perks

Annual incentive reference value of 15%
Full range of medical, financial, and/or other benefits, dependent on the position
Equal Opportunity Employer