# Senior Manager, AI & Analytics Engineering at Coca-Cola

Coca-Cola is hiring a Senior Manager, AI & Analytics Engineering in Atlanta, United States. It pays $143k-$169k a year and Level rates it Works on AI ●●●○; you can [apply on Coca-Cola](https://jobsbylevel.com/go/049815c5-1572-4e6f-ac10-4df425baaef1?utm_medium=ai-agent).

AI Level 3, AI centrality 68 out of 100. US - GA - Atlanta.

## Details

- Company: [Coca-Cola](https://jobsbylevel.com/companies/coca-cola)
- AI level: AI Level 3 (score 68 out of 100)
- Location: US - GA - Atlanta
- Salary: $143k-$169k
- Posted: October 30, 2026
- Apply: https://jobsbylevel.com/go/049815c5-1572-4e6f-ac10-4df425baaef1?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=senior-manager-ai-analytics-engineering-at-coca-cola-dcd6d4

## Prepare for this job

The job page lists 5 likely interview questions for this offer, with a CV checklist: https://jobsbylevel.com/jobs/senior-manager-ai-analytics-engineering-at-coca-cola-dcd6d4

## Description

Job Description Summary: The Senior Manager, AI & Analytics Engineering will be a hands-on technical leader who turns high-value business and analytical problems into production agents and analytical solutions. The team is building for more than 1,000 users across Commercial, Strategy, Customer, Marketing, Category Advisory, and Executive Leadership. This person will partner across those groups and with analytics, data science, engineering, and product teams to identify opportunities, design practical approaches, build working capabilities, and drive adoption across North America. The role combines applied AI, analytics engineering, and system design. This person will build agents and analytical applications while strengthening the reusable services, governed data access, evaluation, security, observability, and deployment patterns behind them. They will balance speed and business value with analytical integrity, reliability, scale, and cost. What You'll Do for Us: Build AI and analytics solutions that create value Partner with business leaders to identify and prioritize high-value use cases, then translate ambiguous questions and analytical needs into clear solution designs, working prototypes, and production capabilities used in real decisions and workflows. Personally build AI agents, analytical applications, and supporting services; own delivery from opportunity framing and architecture through testing, deployment, adoption, and improvement. Choose the right approach for the problem, combining deterministic analytics, machine learning, retrieval, large language models, and agentic workflows where each adds value. Connect AI with trusted analytics Partner with business experts, analysts, data scientists, and data engineers to preserve business definitions, metric grain, filters, source, freshness, lineage, and authorization in AI-enabled analysis. Integrate solutions with Microsoft Fabric, OneLake, Lakehouses, Warehouses, Power BI semantic models, Azure Machine Learning, Azure AI Search, and other approved enterprise capabilities. Build secure, parameterized APIs and tools, including MCP-compatible services, that connect agents to governed data, analytical methods, applications, and business workflows. Strengthen the reusable engineering foundation Build reusable patterns for model access, orchestration, retrieval, context and memory, tool execution, structured responses, human approvals, workflow recovery, and automation. Engineer production Python and API services with automated testing, CI/CD, monitoring, and clear operational ownership; design for performance, concurrent demand, reliability, scale, and cost efficiency. Evaluate frameworks and managed services through working prototypes and measurable trade-offs, using pragmatic architecture that avoids unnecessary complexity and lock-in. Ensure quality, governance, and continuous improvement Build evaluation and regression capabilities using benchmark datasets, known-answer tests, adversarial scenarios, release gates, end-to-end tracing, and production telemetry. Measure analytical accuracy, task completion, adoption, latency, throughput, reliability, token and compute use, and cost per successful workflow; use the evidence to improve solutions through controlled, versioned releases. Implement secure identity, authorization, guardrails, audit logging, human review, and responsible AI controls in partnership with Architecture, Security, Privacy, and Data Governance teams. Provide hands-on technical leadership Operate as a player-coach: contribute production code, lead system-design decisions, review code and architecture, mentor engineers, and establish practical standards that improve delivery across the team. Explain technical choices, risks, and trade-offs clearly to business and technical stakeholders, and help teams turn emerging AI capabilities into useful, supportable products. Qualifications & Requirements: Bachelor’s degree in Computer Science, Software

The description is cut here. Read the full offer: https://jobsbylevel.com/jobs/senior-manager-ai-analytics-engineering-at-coca-cola-dcd6d4

Source: https://jobsbylevel.com/jobs/senior-manager-ai-analytics-engineering-at-coca-cola-dcd6d4

## Cite this page

Level. https://jobsbylevel.com/jobs/senior-manager-ai-analytics-engineering-at-coca-cola-dcd6d4.

Get job alerts: https://jobsbylevel.com/newsletter