Senior Manager, AI & Analytics Engineering

0101 Coca-Cola North America; Atlanta (GA); On-site; USD 143,000 - 169,000; Full time

Job summary

The Coca-Cola North America seeks a Senior Manager, AI & Analytics Engineering in Atlanta to lead hands-on development of AI agents and analytics applications serving 1,000+ users across Commercial, Strategy, Customer, Marketing, and Leadership teams.

You will collaborate with analytics, data science, engineering, and product teams to design, build, and deploy scalable solutions while ensuring governance, security, and cost efficiency.

Qualifications

• Eight+ years of experience in AI, software, data, or ML engineering delivering user-facing solutions.
• Hands-on building and shipping AI/analytic products using Python, SQL, and APIs.
• Experience with large language models or agentic workflows.

Responsibilities

• Identify and prioritize high-value use cases with business leaders.
• Architect and ship AI agents, analytics apps, and supporting services.
• Lead delivery from opportunity framing to deployment and adoption.
• Ensure governance, security, observability, and scalable deployment.

Skills

Python

SQL

APIs

LLMs

Agent frameworks

Education

Bachelor’s degree in Computer Science or related field

Tools

Azure

Power BI

Azure ML

Job 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 Engineering, Data Science, Information Systems, Engineering, Analytics, or a related field, or equivalent practical experience.
• Eight or more years of experience across AI, software, data, platform, analytics, or machine-learning engineering, shipping solutions that serve users.
• Recent hands-on experience personally building and shipping AI, analytical, machine-learning, or data products using Python, SQL, APIs, or comparable tools, plus practical exposure to large language models or agentic workflows.
• Strong analytical reasoning and experience with SQL-based data systems, semantic models, Lakehouse architecture, governed data products, or comparable enterprise analytical environments.
• Sound cloud and system-design fundamentals, including testing, asynchronous workloads, security, observability, reliability, deployment, performance, scalability, and cost management.
• Ability to take an ambiguous problem from business need through architecture, implementation, and adoption while influencing engineering, data science, analytics, security, and business teams.

Preferred Experience:

• Microsoft Fabric, OneLake, Power BI semantic models, Azure Machine Learning, Microsoft Foundry/Azure OpenAI, Azure AI Search, and related Azure services.
• Hands-on experience with AI development tools and platforms such as OpenAI Codex, Anthropic Claude, Azure OpenAI, or comparable enterprise-approved capabilities.
• Modern agent frameworks and interoperability patterns such as LangGraph, LangChain, Microsoft Agent Framework, Semantic Kernel, PydanticAI, MCP, or A2A.
• MLOps, LLMOps, or AgentOps practices covering evaluation, experimentation, deployment, observability, governance, and production operations.
• Building and scaling AI or analytical products in a complex enterprise with multiple business domains, sensitive data, and diverse users.

Pay Range:

United States: 143,400 - 169,300 USD Base pay offered may vary depending on geography, job-related knowledge, skills, and experience.

A full range of medical, financial, and/or other benefits, dependent on the position, is offered.

Annual Incentive Reference Value Percentage:

15 Annual Incentive reference value is a market-based competitive value for your role. It falls in the middle of the range for your role, indicating performance at target.

Location(s):

United States of America City/Cities: Atlanta Travel Required: 00% - 25% Relocation Provided: No Job Posting End Date: November 6, 2026

Our Purpose and Growth Culture:

We are taking deliberate action to nurture an inclusive culture that is grounded in our company purpose, to refresh the world and make a difference. We act with a growth mindset, take an expansive approach to what’s possible and believe in continuous learning to improve our business and ourselves. We focus on four key behaviors – curious, empowered, inclusive and agile – and value how we work as much as what we achieve. We believe that our culture is one of the reasons our company continues to thrive after 130+ years. Visit Our Purpose and Vision to learn more about these behaviors and how you can bring them to life in your next role at Coca-Cola.

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity and/or expression, status as a veteran, and basis of disability or any other federal, state or local protected class.

When we collect your personal information as part of a job application or offer of employment, we do so in accordance with industry standards and best practices and in compliance with applicable privacy laws.

The Coca-Cola Company is a global community of passionate employees who are refreshing the world and making a difference every day. Innovation has been at the heart of our story since 1886. It goes beyond new flavors and brands. Learn more about our system and how we’re making an impact. As a global organization, we seek opportunities to embrace and champion progress. Our careers span across functions and are globally connected to give you an unmatched career experience. We’re glad you’ve chosen to explore your next career opportunity with The Coca-Cola Company. Learn more about our hiring process and pick up tips on how to showcase your experience and skills so you can stand out and thrive. The Coca-Cola global business system is composed of The Coca-Cola Company (TCCC), its subsidiaries and 225 bottling partners around the world. Search jobs throughout our system.