Senior Manager, AI Cloud Innovation Engineer

AI & Cloud Innovation Engineer

Location: Atlanta, GA (Global HQ) - hybrid, onsite 3 days week Estimated Travel: 0-10% Direct Reports: None

The Global Equipment Platforms (GEP) team is seeking an exceptional and forward-thinking AI & Cloud Innovation Engineer to spearhead the exploration, prototyping, and strategic integration of cutting-edge Artificial Intelligence and advanced cloud capabilities for The Coca-Cola Company's global fleet of 17MM+ connected equipment.

Reporting to the AI & Digital Innovation Lead within GEP Digital, Data, & AI, this individual contributor role is pivotal in transforming the insights generated by our Data Scientists into tangible, deployed capabilities that reduce operating expenses, increase revenue, and provide unprecedented real-time market understanding.

You will be responsible for researching, experimenting with, and building proofs-of-concept (POCs) utilizing nascent AI technologies (e.g., advanced Generative AI applications, cutting-edge computer vision techniques, responsible AI frameworks, sophisticated AI Agents) and novel cloud architectures (e.g., edge computing for IoT, serverless AI patterns, highly distributed compute models on Azure). This role demands deep technical expertise in both AI and cloud environments, coupled with a relentless curiosity and a proven ability to translate abstract ideas into tangible, demonstrable prototypes.

Your work will directly inform the future roadmap of our Unified IoT solution, ensuring we can strategically leverage breakthroughs to further reduce TCO, increase transactions, and generate unparalleled real-time insights from our KO Operating System (KOS)-powered devices across a multi-tenant global landscape.

Key Responsibilities

• AI/ML Model Implementation & MLOps (40%)
• AI Infrastructure & Ecosystem Integration (25%)
• Advanced AI Exploration & Transformation (20%)
• Performance Monitoring & Optimization (15%)

Key Deliverables

Robust, scalable, and highly available MLOps pipelines for the GEP AI ecosystem. Production-ready deployed AI/ML models (e.g., predictive maintenance, computer vision, AI Agents) delivering measurable business value. Optimized AI inference services with clear APIs for application integration. Comprehensive monitoring and alerting frameworks for deployed AI solutions. Documented AI engineering best practices, architecture patterns, and deployment guides. Successful enablement and adoption of AI-powered features by internal and external stakeholders.

Decision Rights

Technical design and implementation details for MLOps pipelines and AI model serving infrastructure. Selection of specific AI engineering tools and libraries (within approved Azure ecosystem guidelines). Optimization strategies for AI model performance, cost, and reliability in production.

Required Experience & Qualifications

Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related quantitative field. Master’s or Ph.D. preferred. 7+ years of hands-on experience in AI/ML engineering, MLOps, or productionizing machine learning models in cloud environments. Expert-level proficiency in designing, building, and operating production-grade AI/ML pipelines on Microsoft Azure (e.g., Azure Machine Learning, Azure Kubernetes Service, Azure Functions, Azure Databricks). Strong software engineering background with extensive experience in Python, including developing robust, production-quality code and APIs. Proficiency with containerization technologies (Docker) and orchestration platforms (Kubernetes). Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and deploying models trained with these frameworks. Solid understanding of cloud infrastructure concepts, networking, and security best practices relevant to AI deployments. Experience with Git and CI/CD tools (e.g., Azure DevOps, GitHub Actions). Familiarity with IoT, telemetry data, and embedded systems (exposure to KOS or similar OS is a plus). Proven ability to work independently and drive technical projects from conception to production.

Competencies

Engineering Excellence: Possesses deep software engineering principles and applies them rigorously to build robust, scalable, and maintainable AI solutions. AI Vision & Execution: Translates strategic AI concepts into practical, deployable systems, bridging research with real-world application. Problem Solver & Innovator: Tackles complex technical challenges in AI deployment, consistently seeking and implementing innovative solutions. Collaborative Integrator: Works effectively across diverse technical teams (Data Science, Data Engineering, IT) and with business stakeholders to ensure seamless AI integration. Results-Driven & Accountable: Focuses on delivering tangible business value through deployed AI, taking ownership of the end-to-end operational success of solutions. Continuous Learner: Stays abreast of the rapidly evolving AI landscape and proactively adopts new technologies and best practices.

Success is measured by:

Productionized AI Solutions: Number and diversity of AI/ML models, AI Agents, or computer vision solutions successfully deployed and operating in production. Operational Performance: Uptime, latency, and throughput of deployed AI services; adherence to defined SLAs. Cost Efficiency: Optimization of compute and storage costs for AI workloads in production. Business Impact: Measurable contribution to TCO reduction, revenue uplift, and enhancement of real-time market insights via AI-powered features. Deployment Velocity: Reduction in time from model readiness to production deployment. Model Reliability: Reduction in production incidents related to AI model serving and performance.

What We Can Do For You

Iconic & Innovative Brands: Our portfolio represents over 250 products with some of the most popular brands in the world, including Coca-Cola, Simply, Fairlife & Topo Chico.

Expansive & Diverse Customers: We work with a diversified group of customers which range from retail & grocery outlets, theme parks, movie theatres, restaurants, and many more each day.

All persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form (Form I-9) upon hire. Pay Range: $131,000 - $153,000 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. 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.