Senior Manager, AI Engineer

At Coca-Cola, this onsite Senior Manager role focuses on designing, building, deploying, and operating production-grade AI solutions and AI agents across the company’s digital product portfolio in cloud environments. You will work hands-on with GenAI and agentic frameworks, applying MLOps/LLMOps/AgentOps practices to connect enterprise systems, monitor performance, and enforce safety controls.

Location: Atlanta, GA (onsite). Employment: All applicants must be currently authorized to work in the United States on a full-time basis and must not require Coca-Cola Company sponsorship.

What you’ll do

• Develop and deploy AI agents and GenAI solutions by prototyping, iterating, and moving domain-specific agents into production for information gathering, insight generation, and intelligent action.
• Design AI agents using open interoperability standards such as Model Context Protocol (MCP) and Agent-to-Agent (A2A) to securely connect agents with enterprise data, tools, and external systems, enabling coordinated multi-agent workflows across business domains.
• Write production-grade AI code by producing well-tested, maintainable engineering outputs in Python and other relevant languages.
• Optimize AI models and inference pipelines for performance, reliability, and cost efficiency at scale.
• Deploy and operate AI solutions on Azure, including monitoring and ongoing optimization of AI agents and models.
• Build and maintain MLOps pipelines that cover model training, versioning, inference, and CI/CD.
• Ensure high availability, scalability, and end-to-end observability for AI products running in production.
• Integrate AI capabilities into enterprise platforms by collaborating with Application Engineering and Data Engineering squads to embed AI outputs into product workflows, APIs, and user-facing features.
• Implement AI observability and telemetry for production AI agents and LLM applications, including tracing, reasoning paths, token consumption, latency, cost, output quality, and guardrail violations.
• Build agent evaluation frameworks, including evaluation pipelines, harnesses, benchmark datasets, regression tests, and automated quality scoring.
• Engineer enterprise AI context with retrieval pipelines using enterprise semantic layers, knowledge graphs, vector search, and business ontologies.
• Implement AI safety and runtime controls such as policy enforcement, human-in-the-loop workflows, autonomy thresholds, prompt injection defenses, and secure tool execution.
• Design and orchestrate multi-agent systems for coordinated planning, reasoning, tool execution, and human collaboration.
• Operate LLM and agent-powered applications using modern LLMOps and AgentOps practices, including prompt versioning, evaluation, experimentation, routing strategies, and production lifecycle management.
• Support enterprise digital twin capabilities by integrating operational, commercial, and enterprise data into simulations, predictions, and decision-support workflows.
• Collaborate within agile teams by contributing to sprint planning, backlog refinement, technical design, code reviews, and cross-squad problem-solving.
• Maintain technical currency through continuous learning and integration of advances in AI, machine learning, and Generative AI.
• Conduct rigorous testing and validation to support reliability, accuracy, and explainability of AI agents and outputs.
• Share knowledge through internal documentation, code reviews, and engineering best practices.

What you bring

• 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 AI or ML engineering experience with a track record of taking AI models and solutions from development to production.
• Strong proficiency in Python, with working knowledge of additional languages such as Java or C++.
• Experience building and deploying LLM-powered and agentic AI applications in production using frameworks such as LangChain, LangGraph, CrewAI, Semantic Kernel, Model Context Protocol (MCP), Agent-to-Agent (A2A), or similar.
• Cloud experience deploying and operating AI/ML solutions with 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 into enterprise applications.
• Experience with MLOps/LLMOps/AgentOps, including model and prompt versioning, evaluation, experimentation, routing strategies, observability, cost optimization, and production lifecycle management.
• Strong software engineering fundamentals, including API design, testing, version control, CI/CD, containerization with Docker and Kubernetes, and AI system deployment and monitoring.
• Experience in Agile delivery environments, including sprint execution, code review, and cross-squad collaboration.
• Experience implementing responsible AI practices such as runtime guardrails, AI safety controls, model explainability, data privacy, and secure agent execution.
• Experience implementing AI observability and telemetry for tracing, reasoning diagnostics, token consumption, latency, cost, output quality, and runtime performance.
• Strong analytical and problem-solving skills, including translating business requirements into well-scoped AI solutions with Technical Leads and Product teams.
• Excellent communication skills to explain AI products and trade-offs to technical and non-technical stakeholders.

Technologies

• Python, Java, C++
• LangChain, LangGraph, CrewAI, Semantic Kernel
• Model Context Protocol (MCP), Agent-to-Agent (A2A)
• Azure, AWS, GCP
• Vector databases, embeddings, Retrieval-Augmented Generation (RAG), GraphRAG
• RESTful APIs, MLOps, LLMOps, AgentOps
• Docker, Kubernetes

Compensation and terms

• Salary range (US): USD 152,000 - 178,300 per year
• Annual incentive reference value: 15%
• Long-term incentive reference value: 0% - 20%
• Travel required: 0% - 25%
• Relocation provided: No
• End date: September 27, 2026

Purpose and growth culture

Coca-Cola is taking deliberate action to nurture an inclusive culture grounded in its purpose to refresh the world and make a difference.