AWS AI Cloud Engineer

Key Responsibilities

• Cloud Architecture & Evaluation: Assess and analyze existing AWS landscapes against the AWS Well-Architected Framework to identify gaps and recommend strategic improvements.
• Infrastructure Design: Architect and develop secure, scalable, and resilient cloud applications utilizing core AWS services.
• DevOps & Automation: Design, implement, and maintain robust CI/CD frameworks to streamline application deployment.
• Scripting & Tooling: Build automation scripts and infrastructure-as-code solutions to eliminate manual processes and improve operational efficiency.

Required Skills & Qualifications

• AWS Expertise: Deep, hands-on experience architecting and developing with core AWS services, including S3, Lambda, EC2, VPC, and IAM.
• CI/CD Tools: Strong experience with Azure DevOps (ADO) or similar tools like Jenkins for continuous integration and delivery.
• Automation & Scripting: Strong understanding of automation using Python and the Boto3 library.
• Methodologies: Solid understanding of modern CI/CD principles, DevOps culture, and agile methodologies.

Nice to Have / Preferred Qualifications

• Experience or core knowledge of generative AI tools, specifically AWS Bedrock and AI Agents.
• Application Development: Core software development experience using languages such as Python, Java, or equivalent will be nice to have
• Relevant certifications, such as AWS Certified Solutions Architect Professional or AWS Certified DevOps Engineer – Professional.