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Senior Manager, AI Engineer

Coca-Cola Atlanta, GA

Atlanta, GA

Today

$152k - $178k/yr Full time Manager Agentic Ai Agentops

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Job Description

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.

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