Advanced Platform Architect

2 days ago

Belgaum, Karnataka, India beBeeCloudNative Full time ₹ 20,00,000 - ₹ 30,00,000

Seeking a Platform Engineer to join our dynamic team as an Architect. In this role, you'll design, develop and maintain cutting-edge build and test environments for critical GenAI workloads on cloud infrastructure.

You'll partner with architects to design robust systems while providing crucial development support to SRE/Operations teams tackling complex distributed systems challenges at scale. We're seeking an engineer who champions Cloud-Native development, emphasizing Kubernetes.

Key Responsibilities:

  • Designing state-of-the-art GPU compute clusters to support critical workloads.
  • Implementing comprehensive automated testing strategies and frameworks across unit, integration, API and end-to-end levels for 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.
  • 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.

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.

Preferred Qualifications:

  • 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.

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