This role pays less than
81%
of similar roles. Most pay
$174,912–$246,150
— the shaded band above.
At the midpoint, this role pays about
$165k
versus about
$211k
for comparable roles.
Based on 240 similar postings.
Employer
About The Coca‑Cola Company
The Coca-Cola Company is the world''s largest beverage company, producing and distributing iconic soft drinks, juices, water, and other beverages across more than 200 countries. Industry: Beverages & Consumer Goods
The Coca‑Cola Company currently has
12 open roles
on FindRole.
Listed pay typically runs
$152,000–$178,300
across 12 roles with salary data.
As part of the Product & Engineering team within the Global Digital Network, the Senior Manager, AI Engineer will design, build, and deploy production-grade AI solutions across a diverse digital product portfolio. This hands-on role involves developing domain-specific AI agents, integrating GenAI and agentic frameworks into enterprise platforms, and managing MLOps pipelines on Azure cloud infrastructure. The candidate will write high-quality Python code to optimize inference pipelines, implement retrieval systems using vector databases and knowledge graphs, and establish robust evaluation frameworks for accuracy and safety. Key technical requirements include experience with LangChain, LangGraph, CrewAI, and Model Context Protocol. The role focuses on solving complex business problems by transforming data science prototypes into reliable products while ensuring high availability, observability, and secure execution within a fast-moving agile environment to support enterprise digital twin capabilities and automated workflows.
Develop, prototype, and deploy production-grade AI agents and GenAI solutions across the enterprise portfolio.
Design multi-agent systems using interoperability standards like MCP to connect agents with enterprise data and tools.
Write and optimize high-quality, maintainable Python code for AI models and inference pipelines.
Manage MLOps and AgentOps workflows including model versioning, CI/CD pipelines, and cloud infrastructure deployment on Azure.
Build evaluation frameworks and automated quality scoring to assess agent accuracy, safety, and performance.
Engineer retrieval pipelines using vector search, knowledge graphs, and semantic layers to ground AI in enterprise context.
Implement observability and telemetry for LLM applications to monitor token usage, latency, and guardrail violations.
Establish AI safety controls including prompt injection defenses and human-in-the-loop workflows.
What we're looking for
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 track record of moving models from development to production.
Strong proficiency in Python and working knowledge of other languages like Java or C++.
Experience building and deploying LLM-powered and agentic AI applications using frameworks such as LangChain, LangGraph, CrewAI, or Model Context Protocol (MCP).
Experience with vector databases, embeddings, Retrieval-Augmented Generation (RAG), GraphRAG, and context engineering.
Experience with MLOps, LLMOps, or AgentOps practices including model versioning, evaluation, observability, and cost optimization.
Strong software engineering fundamentals including API design, testing, CI/CD, Docker, Kubernetes, and monitoring.