GCP Infrastructure Engineer - Google Cloud, Terraform, Python, Bash, GKE, CI/CD

The GCP Infrastructure Engineer will design, build, and manage the cloud infrastructure powering Generative AI (GenAI) applications at scale. This role involves owning the end-to-end infrastructure lifecycle, from design and provisioning to automation, monitoring, and optimization, enabling data scientists and ML engineers to deploy GenAI workloads effectively.

Key Responsibilities:

• Cloud Infrastructure: Provision and maintain scalable, secure infrastructure for GenAI on GCP, including GPU/TPU clusters for distributed training and inference.
• Automation & Reliability: Develop IaC templates using Terraform, implement GitOps practices, and build CI/CD pipelines for model workflows while applying SRE principles.
• Security & Governance: Embed DevSecOps practices, manage identity and access, and ensure compliance with standards like HIPAA, SOX, and GDPR.
• Monitoring: Implement observability stacks (Prometheus, Grafana, Datadog) to track infrastructure health and ML-specific metrics like model drift.
• Collaboration: Partner with cross-functional teams to streamline GenAI development and provide reusable infrastructure templates.

Required Qualifications

• Bachelor’s or master’s degree in Computer Science, Software Engineering, or related field.
• 8+ years of experience in cloud infrastructure engineering, DevOps, or platform engineering.
• Strong expertise in GCP, Vertex AI, Docker, Kubernetes (GKE), and container orchestration.
• Proficiency in Python and Bash scripting.
• Experience with CI/CD tools (GitHub Actions, Jenkins) and IaC tools (Terraform).
• Familiarity with data pipelines (Dataflow, Kafka).

Preferred Qualifications

• Experience in MLOps, multi-cloud environments, and feature stores (Vertex AI Feature Store, Feast).
• Knowledge of distributed training frameworks (DeepSpeed, PyTorch Distributed).
• Relevant certifications such as Google Cloud Professional Cloud Architect or Machine Learning Engineer.