Job Description

Job Description

Design and Deploy: Contribute to the design and deployment of enterprise-wide scalable, highly available, secure, and reliable platforms and architecture on the Google Cloud Platform (GCP) full-stack as well as AL solutions and ML pipelines
Establish Reusable Patterns: Develop reusable patterns to be used across engineering teams, ensuring consistency and efficiency and apply these patterns to AI and ML workflows.
Collaborate: Work closely with various business and technology teams to create a clear and cohesive vision for the future state of our Google Cloud Platform.
Stay Informed: Maintain awareness of industry trends and technologies, recommending timely adjustments to strategies as appropriate and stay up to date on AI and ML advancements.
Security & Governance: Assist with the development and management of security and governance processes to ensure that cloud deployments are secure and follow industry best practices.

Technical Experience and Qualifications:

We value candidates who have a thinker/doer mentality. A willingness to learn and grow is critical to success.

Experience: 4+ years of relevant work experience in cloud engineering.
AI Platforms: Understanding of AI platforms in a cloud environment (Vertex AI, CoPilot, Sagemaker, Bedrock).
Cloud Platform: Proficiency in Cloud Platforms with an understanding of Google Cloud Platform (GCP)
Infrastructure as Code: Intermediate proficiency in Terraform for infrastructure automation.
Network and Security: Advanced understanding of network and security principles.
Linux: Advanced knowledge of Linux operating systems (RHEL).
DevSecOps: Advanced skills in DevSecOps practices, with a focus on shift-left thinking and zero-touch automation.
Architecture Patterns: Strong experience working with common architecture patterns and an understanding of AI/ML workflows.
Programming: Basic knowledge of programming languages like Python.
BDD: Strong experience with Behavior Driven Development (BDD) creation for testing.