Duties and Responsibilities
- Develop, deploy, and operate enterprise AI systems, APIs, and model-serving infrastructure that support retail operations at scale, including personalization, forecasting, pricing intelligence, and real-time decisioning across stores, digital channels, and supply chain systems.
- Work closely with data scientists, AI engineers, and application teams to integrate, deploy, and support AI capabilities within customer-facing and internal systems, including mobile applications.
- Translate AI solutions and business requirements into production-ready implementations, ensuring alignment with organizational standards and roadmaps defined by the Manager of AI Implementation and Strategy.
- Build, deploy, and maintain end-to-end AI pipelines, including data ingestion, feature engineering workflows, model training orchestration, deployment, and monitoring in production environments.
- Own the operational reliability of AI platforms and services, including uptime, performance, security, and cost optimization.
- Provision, configure, and maintain scalable AI and machine learning environments in Microsoft Azure and Databricks to support enterprise AI initiatives.
- Support, monitor, and troubleshoot cloud-based services integrated with POS systems, ensuring high availability and responsiveness.
- Implement and maintain infrastructure-as-code (IaC), CI/CD pipelines, and automation practices for AI workloads across Azure and Databricks environments.
- Monitor system health, model performance, and data pipelines, and proactively resolve issues, optimize workloads, and implement improvements.
- Ensure all solutions adhere to enterprise governance, security, and data management policies, including access controls, data privacy, and compliance standards.
- Create and maintain technical documentation, runbooks, and operational procedures to support system maintainability, incident response, and knowledge transfer.
- Collaborate with architecture and strategy teams by providing feedback from operational experience to improve system design, scalability, and maintainability.
EDUCATION AND EXPERIENCE
- Bachelors degree in Computer Science or related field (preferred)
- 5+ years of experience in Cloud Engineering (preferred)
