AI Cloud Engineer

Dear Candidate,

Greetings from TATA Consultancy Services!!

Thank you for expressing your interest in exploring a career possibility with the TCS Family.

Hiring For:- AI Cloud Engineer

Location: PAN INDIA

Experience: 5 to 8yrs

ob 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.