Master Cloud Engineer

Job Overview

We are seeking a highly skilled Cloud Architect to join our team. As a Cloud Architect, you will design and develop cutting-edge cloud infrastructure for critical workloads.

You will partner with architects to create robust and scalable systems, providing crucial development support to SRE/Operations teams as they tackle complex distributed systems challenges at scale.

We seek an engineer who champions cloud-native development, with a particular emphasis on Kubernetes.

Key Responsibilities:

• Designing state-of-the-art GPU compute clusters to support critical workloads.
• Developing comprehensive automated testing strategies and frameworks across unit, integration, API, and end-to-end levels for critical commerce flows.
• Developing robust performance testing frameworks to validate platform scalability, resilience, and identify optimization opportunities.
• Planning of comprehensive monitoring solutions with alerting systems to track platform health and ensure SLA compliance.
• Designing specialized test frameworks for security controls and ensuring compliance validation across payment and personal data.
• Architecting a scalable automation infrastructure that supports growing platform capabilities with consistent test environments.
• Troubleshooting, diagnosing, and performing root cause analysis of system failures, isolating components and failure scenarios in collaboration with internal and external partners.
• Optimizing cluster operations for maximum reliability, efficiency, and performance.

Requirements:

• Over 6-8 years of experience working with developing ML Infrastructure.
• Over 3 years of hands-on experience in large-scale direct experience building and deploying production-ready services on Kubernetes.
• A proven history of engaging with and contributing to open-source projects.
• A collaborative spirit, demonstrated by prior work developing scalable software solutions for cloud services.
• The ability to effectively communicate complex technical designs and quality approaches across various mediums.
• A deep understanding of GPU computing and AI infrastructure.
• A strong passion for solving complex technical challenges and optimizing system performance.
• Working knowledge of cluster configuration management tools such as BCM or Ansible, and infrastructure-level applications including Kubernetes, Terraform, and MySQL.
• In-depth understanding of container technologies like Docker and Containers.
• Proficiency in programming with Python and Bash scripting.

Benefits:

• Significant experience with sophisticated infrastructure tooling, including Kubernetes Cluster API, Terraform, Helm, and Operator Framework.
• Practical, production-level experience across major cloud platforms: Azure, Google Cloud Platform (GCP), or Amazon Web Services (AWS).
• Ability to adapt to new technologies and Frameworks in ML/GenAI landscape.
• A strong track record of successfully refactoring and optimising software for deployment within Kubernetes environments.
• Comfort discussing and working with core Kubernetes concepts like CSI, CNI, and CRI.
• Comprehensive understanding of the CNCF landscape and its associated tooling.
• The ability to decompose complex problems into simpler sub-problems and leverage existing solutions for efficient implementation, along with designing simple, self-sustaining systems.
• Experience leveraging AI/ML to proactively detect and resolve incidents, automate alert triaging, perform log analysis, and streamline repetitive workflows.