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Senior Systems Architect
3 weeks ago
We are seeking a skilled professional to fill the role of Platform Engineer. In this position, you will be responsible for designing, implementing and optimizing our infrastructure.
As a key member of the team, your responsibilities will include:
- Designing and implementing cutting-edge 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.
- Designing robust performance testing frameworks to validate platform scalability, resilience and identify optimization opportunities.
- Planning 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 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.
Key requirements for this role include:
- 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.
Additional desirable skills include:
- 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.