# RGM Product Manager at Coca-Cola

Coca-Cola is hiring an RGM Product Manager in Atlanta, United States. It pays $202k-$229k a year and Level rates it Works on AI ●●●○; you can [apply on Coca-Cola](https://jobsbylevel.com/go/00b7e0f2-82e7-4758-9560-7c0ac56de4e3?utm_medium=ai-agent).

AI Level 3, AI centrality 77 out of 100. US - GA - Atlanta.

## Details

- Company: [Coca-Cola](https://jobsbylevel.com/companies/coca-cola)
- AI level: AI Level 3 (score 77 out of 100)
- Location: US - GA - Atlanta
- Salary: $202k-$229k
- Posted: November 6, 2026
- Apply: https://jobsbylevel.com/go/00b7e0f2-82e7-4758-9560-7c0ac56de4e3?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=rgm-product-manager-at-coca-cola-6f0faa

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## Description

Job Description Summary: LOCATION: THE INCUMBENT CAN BE BASED IN ATLANTA, GA OR SINGAPORE About the Role Revenue Growth Management (RGM) is one of The Coca-Cola Company’s most important commercial capabilities, and not simply a pricing discipline. Coca-Cola positions RGM alongside brand building, innovation, and integrated execution as a core capability for topline growth, and our growth strategy names it a key commercial capability for determining where to play and how to win. RGM connects consumer demand to the economics of the system. It determines what we sell, in which packages, at what price points, through which channels and customers, and with what promotional investment, all in service of balanced growth across transactions, volume, and price/mix. Done well, it finds incremental revenue pools and converts them into commercial action, improves the economics of every price, pack, assortment, and promotion decision, builds the affordability and premiumization ladders that bring more consumers into the portfolio, and gives Coca-Cola and its bottlers a common fact base for growing customer revenue and profit rather than simply negotiating price. We are now reimagining RGM for the agentic AI era, and we are building it ourselves. Our Global RGM Product is evolving from a suite of analytical solutions into an intelligent decision platform where AI agents interact directly with enterprise data, invoke advanced analytics and optimization models, run and compare scenarios, and hand commercial teams a recommendation with the reasoning attached. Work that once took an analyst a week (pulling the data, running the model, writing the story, defending the number) is being compressed into a conversation. Few companies are attempting this at this scale, and fewer are still against decisions this consequential: real pricing, promotion, and portfolio moves, made across markets and bottlers. The work sits at the frontier of the CPG industry, spanning agent orchestration, retrieval over enterprise data, and the evaluation of non-deterministic and deterministic systems, and none of it is a research exercise. What we build ships to commercial teams who use it to make decisions the same week. This is an opportunity to build, not just design, the next generation of commercial decision intelligence at Coca-Cola, and to establish the operating model for agentic RGM at global scale. The patterns set here will shape how one of the world’s largest commercial systems makes its most important decisions. If you want your work in front of real users, at real scale, from the first release, this is that role. Role Overview As Product Manager, RGM, you will own the what and the why of how AI shows up in the Global RGM product: which commercial decisions agents should support, for whom, in what order, and how success is measured in commercial impact, adoption, and responsible delivery. You will work within a persistent, cross-functional product team alongside Data Science, Engineering, UX, Architecture, and RGM experts. Engineering owns how the product is built; you own everything that determines whether it is worth building. Product direction starts in market. You will spend time with RGM teams at operating units and bottlers to understand how pricing, promotion, and portfolio decisions are actually made, where current ways of working break down, and where AI can credibly change the outcome. You will convert that discovery into direction: clear problem statements, an 18-month AI product roadmap, and requirements that tell the team not just what to build, but why it matters commercially. Day to day, this is a hands-on AI product seat. You will write user stories, acceptance criteria, and evaluation criteria for agent behavior, prioritize the backlog against commercial value, define what “good” looks like for each release (including the quality bar for AI outputs), and sign off that what shipped does what the business needed. It demands deep technical

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