Job Summary

A GCP Infrastructure AI Engineer with AI specialization (8+ Years) is responsible for architecting, deploying, and managing scalable, secure, and intelligent cloud infrastructure on Google Cloud Platform, integrating advanced AI capabilities such as Gemini Enterprise, prompt engineering, and agentic workflows. This role combines cloud infrastructure expertise with AI service implementations to enable data-driven, automated, and smart business solutions.

This job description caters to organizations seeking specialized engineers who can combine GCP infrastructure management with AI capabilities to drive innovative, automated, and intelligent business solutions on Google Cloud.

Key Responsibilities

• Design, build, and maintain cloud infrastructure leveraging GCP services like Compute Engine, Kubernetes Engine (GKE), Cloud Storage, and BigQuery for robust data and computing workloads.
• Integrate AI technologies using Google’s Gemini Enterprise, Vertex AI Search for advanced large language model (LLM) solutions and AI-driven applications.
• Develop & optimize prompt engineering workflows to create effective AI model interactions tailored to business needs.
• Implement & manage agentic AI workflows that enable autonomous decision-making and process automation within the cloud environment.
• Automate infrastructure & AI pipeline deployments using Terraform &CI/CD pipelines with Cloud Build.
• Apply robust security practices across infrastructure and AI services, including IAM, VPC Service Controls, and data governance compliant with organizational standards.
• Monitor infrastructure and AI system performance using Stackdriver, AI-specific logging, and metric tools to ensure reliability and efficiency.
• Collaborate with data scientists, AI engineers, and DevOps teams to integrate AI models and workflows into cloud solutions.
• Continuously evaluate new GCP AI services and frameworks to innovate and improve enterprise AI capabilities.

Skill Requirements

• Deep proficiency in GCP infrastructure services, network design, and security principles.
• Hands-on experience with Google AI offerings like Gemini Enterprise, Vertex AI, and AutoML.
• Strong knowledge of prompt engineering methods and building intelligent agentic workflows.
• Experience with container orchestration (GKE), serverless technologies, and infrastructure automation tools (Terraform, Cloud Build).
• Familiarity with software development and scripting languages (Python, Bash) to support AI and cloud automation.
• Ability to design scalable, secure, and cost-effective AI-powered cloud infrastructures.
• Strong problem-solving skills in AI model deployment, integration, and cloud infrastructure management.

Other Requirements

• Bachelor’s degree in IT/ Engineering/MBA or other management qualification.
• GCP Associate Engineer / Architect Certification
• Kubernetes Certification [CKA CKAD etc.]
• Terraform Associate