AI Engineer Architect needs 8 years AI/ML development experience AI Engineer Architect requires: Knowledge and implementation experience of AI/ML in AWS Cloud services; Data science and advanced analytics, including knowledge of advanced analytics tools (such as SAS, R and Python); DevOps workflows and tools, such as Git, containers, Kubernetes and CI/CD. Bachelors Degree in a related field (Computer Science, AI/ML). Data science and advanced analytics, including knowledge of advanced analytics tools (such as SAS, R and Python). DevOps workflows and tools, such as Git, containers, Kubernetes and CI/CD. AI Architecture - data management, governance, model building and deployment Knowledge and implementation experience of AI/ML in AWS Cloud services APIs, Apigee, Developer Portals. Expertise in JSON, RESTful services, and similar related tech Containers: Docker, Kubernetes, OpenShift, Ansible, Nexus, Software defined networking. AI Engineer Architect duties: Collaborate with data scientists and other AI professionals Define the feasibility of use cases along with architectural design for the AI platform Select cloud, on-premises or hybrid deployment models, and ensure new tools are well-integrated with existing data management and analytics tools. Work with Business and delivery partners to understand future requirements and implications for architecture