Cloud Infrastructure Architect
2 weeks ago
Key responsibilities of this role include designing, implementing and optimizing cutting-edge infrastructure.
This involves working with architects to design and implement highly robust and scalable systems, as well as providing crucial development support to SRE/Operations teams tackling complex distributed systems challenges at scale.
Another key responsibility is developing robust performance testing frameworks to validate platform scalability, resilience and identify optimization opportunities.
The successful candidate will also be responsible for planning comprehensive monitoring solutions with alerting systems to track platform health and ensure SLA compliance.
Additionally, the position requires designing specialized test frameworks for security controls and ensuring compliance validation across payment and personal data.
Also involved in architecting a scalable automation infrastructure that supports growing platform capabilities with consistent test environments.
Further, troubleshooting, diagnosing and performing root cause analysis of system failures, isolating components and failure scenarios in collaboration with internal and external partners.
Finally, optimizing cluster operations for maximum reliability, efficiency and performance.
Required skills and qualifications 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.
Effective communication of 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.
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.
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.
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.
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