AI Engineer Architect

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.

• Bachelor’s 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

• API’s, 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

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Last updated on Aug 20, 2024