Senior Linux Architect

3 days ago


Ellore, Andhra Pradesh, India beBeeLinuxEngineer Full time ₹ 2,00,00,000 - ₹ 2,50,00,000

Job Summary:

We are seeking a highly skilled Senior Linux Engineer to join our team. This is a unique opportunity to architect, engineer, and automate large-scale High-Performance Computing (HPC) platforms used for quantitative finance and advanced research.

The successful candidate will be responsible for designing and managing HPC environments, researching and experimenting with new centralized multi-tenant clustered platforms, troubleshooting complex issues across storage, OS, and networking layers, building tools to improve performance, monitoring, and automation of HPC clusters, and driving efficiency through automation of provisioning and housekeeping.

This role requires expertise in distributed file systems, strong knowledge of Linux configuration, troubleshooting, and performance tuning, familiarity with x86/AMD platforms optimized for both transaction speed and distributed parallel processing, networking knowledge, experience with Linux software RAID, hardware RAID, erasure encoding, infrastructure automation skills, scripting, protocol knowledge, hybrid and cloud-native HPC deployment experience, familiarity with AWS storage services, knowledge of AI/ML HPC offerings on cloud platforms, experience with HPC job schedulers, and hardware familiarity.

Key Responsibilities:

  • Design and Manage HPC Environments: Design and manage high-performance computing environments that support quantitative finance and advanced research.
  • Research and Experiment with New Platforms: Research and experiment with new centralized multi-tenant clustered platforms to improve performance and efficiency.
  • Troubleshoot Complex Issues: Troubleshoot complex issues across storage, OS, and networking layers to ensure optimal system performance.
  • Build Tools for Performance and Automation: Build tools to improve performance, monitoring, and automation of HPC clusters.
  • Drive Efficiency through Automation: Drive efficiency through automation of provisioning and housekeeping.

Requirements:

  • 5+ Years of Experience: 5+ years of engineering, deployment, and management of large-scale (250+ servers) Linux infrastructure, ideally in financial services or HPC environments.
  • Expertise in Distributed File Systems: Expertise in distributed file systems (Lustre, GPFS) and a variety of filesystems (ZFS, XFS, ext4).
  • Strong Knowledge of Linux: Strong knowledge of Linux (RHEL/CentOS/Ubuntu) configuration, troubleshooting, and performance tuning.
  • Familiarity with x86/AMD Platforms: Familiarity with x86/AMD platforms optimized for both transaction speed and distributed parallel processing.
  • Networking Knowledge: Networking knowledge: 10GE/25GE, InfiniBand, RoCE, RDMA.
  • Experience with Linux Software RAID: Experience with Linux software RAID, hardware RAID, erasure encoding.
  • Infrastructure Automation Skills: Infrastructure automation skills: Terraform, Ansible, Puppet, Chef.
  • Scripting Knowledge: Scripting: Python and Shell.
  • Protocol Knowledge: Protocol knowledge: NFS (v4.1), CIFS, SMB, ACLs.
  • Hybrid and Cloud-Native HPC Deployment Experience: Hybrid and cloud-native HPC deployment experience (AWS preferred).
  • Familiarity with AWS Storage Services: Familiarity with AWS storage services (S3, Storage Gateway, EBS).
  • Knowledge of AI/ML HPC Offerings: Knowledge of AI/ML HPC offerings on cloud platforms (AWS/GCP).
  • Experience with HPC Job Schedulers: Experience with HPC job schedulers (Slurm, Condor, Airflow, SGE).
  • Hardware Familiarity: Hardware familiarity: HPE, Dell, Supermicro systems.

What We Offer:

  • Career Growth Opportunities: Opportunities for career growth and professional development in a fast-paced, innovation-driven environment.
  • Collaborative Team Environment: Collaborative team environment where infrastructure is seen as a strategic enabler, not a back-office function.
  • Exposure to Cutting-Edge Technology: Exposure to cutting-edge HPC, cloud, and AI/ML workloads at scale.


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