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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

Design, build, deploy, and operate production-grade AI solutions and AI agents across Coca-Cola’s digital product portfolio in cloud environments.

Responsibilities

Prototype, iterate, and take to production domain-specific AI agents and GenAI solutions for information gathering, insight generation, and intelligent action
Design and implement agents using interoperability standards including Model Context Protocol (MCP) and Agent-to-Agent (A2A) to securely connect agents with enterprise data, tools, and external systems
Produce production-grade, well-tested, maintainable AI code in Python and other relevant languages
Optimize AI models and inference pipelines for performance, reliability, and cost efficiency at scale
Follow The Coca-Cola Company engineering standards for quality, security, and observability
Deploy, monitor, and optimize AI agents and models on Azure cloud infrastructure
Build and maintain MLOps pipelines covering training, versioning, inference, and CI/CD
Ensure high availability, scalability, and end-to-end observability for AI products 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 agents and LLM applications, including tracing, reasoning paths, token consumption, latency, cost, output quality, and guardrail violations
Build agent evaluation frameworks using evaluation pipelines, harnesses, benchmark datasets, regression tests, and automated quality scoring for accuracy, safety, and business performance
Engineer trusted AI context using retrieval pipelines with enterprise semantic layers, knowledge graphs, vector search, and business ontologies
Implement AI safety and runtime controls, including 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 applications in production using modern LLMOps and AgentOps practices such as prompt versioning, evaluation, experimentation, routing strategies, cost optimization, and lifecycle management
Support enterprise digital twin capabilities by integrating operational, commercial, and enterprise data into simulations, predictions, and decision-support workflows
Collaborate in agile engineering teams through technical design discussions, code reviews, testing, and delivery with Technical Leads, software engineers, data engineers, and other AI Engineers
Participate in sprint planning, backlog refinement, and collaborative problem-solving to deliver high-quality engineering outcomes
Stay current with advances in AI, machine learning, and Generative AI and apply relevant improvements to existing and new solutions
Conduct rigorous testing and validation for reliability, accuracy, and explainability of AI agents and outputs
Share knowledge internally and contribute to code reviews and engineering best practices

Requirements

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 with a demonstrated 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, MCP, A2A, or similar
Experience deploying and operating AI and ML solutions on cloud infrastructure 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 capabilities into enterprise applications
Experience with MLOps, LLMOps, or AgentOps, including model and prompt versioning, evaluation, experimentation, routing strategies, observability, cost optimization, and production lifecycle management
Strong software engineering fundamentals: API design, testing, version control, CI/CD, containerization with Docker and Kubernetes, and model deployment and monitoring
Experience working in Agile delivery environments, including sprint execution, code review practices, 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 (tracing, reasoning diagnostics, token consumption monitoring, latency, cost, output quality, and runtime performance)
Strong analytical and problem-solving skills with the ability to work with Technical Leads and Product teams to translate business requirements into well-scoped AI solutions
Excellent communication skills to explain AI products and trade-offs to technical and non-technical stakeholders

Tech Stack

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

Location and Compensation

Location: Atlanta, GA (onsite)
Salary: USD 152,000 - 178,300 per year (United States)
Annual incentive: reference value 15%
Long-term incentive: reference value 0 - 20%
Travel required: 0% - 25%
Relocation provided: No
Job posting end date: September 27, 2026

Work Authorization

The Coca-Cola Company will not offer sponsorship for employment status (including H1-B visa status)
Applicants must be currently authorized to work in the United States on a full-time basis and must not require sponsorship to continue to work legally in the United States

We are taking deliberate action to nurture an inclusive culture grounded in our company purpose to refresh the world and make a difference.

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