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Cognizant Hiring For HPC , Github Pipelines, AWS

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Hybrid

Cognizant Hiring For HPC , Github Pipelines, AWS

Cognizant

Cognizant Hiring For HPC , Github Pipelines, AWS

Skills

NodePythonGrafanaAIAWSAnsiblePrometheusGitHubLinuxKubernetesTerraform

1 month ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Hybrid

Published on:

15 September 2026

What they need


Cognizant is hiring HPC , Github Pipelines, AWS

Primary & Mandatory Skill: HPC administration & AWS DevOps

Yrs of exp : 5 years to 8 Years

Location : Chennai, Kolkata, Bangalore, Coimbatore, Pune, Hyderabad

Shift timing: 1pm IST to 11pm IST

If you are interested, kindly share the below details along with your updated resume to [email protected]

Please share below details (Mandatory) :

Full Name

Contact number:

Alternative contact number:

Current Location:

Interested Locations:

Total Years of experience:

Relevant years of experience: - HPC , Github Pipelines, AWS

Current company:

Currently working in Permanent or Contract position:

If Contract means mention Pay roll name:

Do you have form 16 for your experience?(Yes or No)

Mention the years as well:

Do you have PF statement for your experience? (Yes or No):

Primary Skill:

Secondary Skill:

Notice period:

NP negotiable: if yes how many days they can negotiate? :

If you are Serving any Notice period Means, please mention Last date of Working:

Holding Offer-

Current CTC-

Expected CTC-

Education -

Detailed JD:

Scope of Work:

HPC Cluster Deployment:

  • Automate the deployment process of HPC clusters using CI/CD pipelines by utilizing GitHub pipeline and AWS Systems Manager.
  • Implement CI/CD pipelines to manage and deploy updates to the HPC cluster efficiently.
  • Set up and configure HPC clusters to meet specific requirements and workloads.
  • Manage and maintain HPC hardware components such as CPUs and GPUs, along with the necessary software.
  • Conduct regression testing to verify the functionality and performance of non-GXP HPC clusters.

Workload Scheduler Management:

  • Install and configure workload managers and schedulers like LSF, SLURM, and PBS Pro.
  • Manage the addition and removal of compute nodes and adjust the priority of master and slave nodes.
  • Develop and manage resource policies and rules to optimize cluster performance.
  • Configure and allocate resources such as CPU and memory, and profile applications for optimal performance.
  • Address and resolve issues related to schedulers, daemons, and license servers.

Network and High-Performance Connectivity Management:

  • Install and configure HPC interconnect networks.
  • Design and configure the network topology for HPC clusters.
  • Ensure the maintenance and monitoring of InfiniBand connectivity.
  • Resolve connectivity issues related to InfiniBand, RoCE, and Ethernet.

Monitoring and Reports:

  • Produce daily health check reports for the HPC cluster.
  • Automate monitoring scripts to streamline the monitoring process.
  • Conduct periodic reviews of reports and audit trails.

OS Administration and Management:

  • Install and configure operating systems for HPC clusters.
  • Address OS-related issues such as CPU, memory, and SWAP utilization, and perform application file system cleanup.
  • Ensure application service continuity by performing pre and post checks from both OS and application perspectives during planned and unplanned outages.

Applications and Tools:

  • Install HPC libraries and tools such as MPI and compilers.
  • Install and configure HPC applications, both commercial off-the-shelf (COTS) and open source, and manage packages using Spack.
  • Apply patches and upgrades to HPC applications.
  • Resolve issues related to HPC applications.

HPC Storage Management:

  • Administer and configure HPC storage systems.
  • Oversee the administration of HPC file systems.
  • Monitor and troubleshoot HPC storage systems.
  • Manage backup and tape library systems.

Below is the key responsibility, essential skills of the resources we will deploy.

Key Responsibilities

  • Cluster Management: Install, configure, and maintain compute nodes, GPUs (NVIDIA), high-speed storage (Lustre, GPFS),

and interconnects (InfiniBand, RoCE).

  • Performance Tuning: Optimize scientific applications, kernels, and workflows for maximum throughput, scalability, and minimal queue times.
  • User Support: Act as a technical expert for researchers, debugging jobs, resolving complex issues, and providing training on tools and best practices.
  • Software Management: Manage workload managers (Slurm, LSF), schedulers, software licensing (FlexLM), OpenPBS,

containers (Singularity), and compilers.

  • Infrastructure: Administer high-speed interconnects (InfiniBand), storage (Lustre, CEPH), and potentially cloud/hybrid solutions.
  • Implement and manage monitoring (Grafana, Prometheus) and orchestration tools (Slurm, Kubernetes).
  • Automation: Develop scripts (Python, Ansible) for provisioning, monitoring, and automating routine tasks.
  • Security & Policy: Implement and enforce security policies, manage user access, and oversee lifecycle management.

Essential Skills & Qualifications

  • Technical Expertise: Strong Linux, Python, scripting (Ansible, Terraform), HPC schedulers (Slurm), networking (InfiniBand), and GPU computing.

Team will have knowledge of Gilead systems and AWS CICD pipelines.

  • HPC Domain Knowledge: Experience with parallel file systems, workload management, and performance analysis tools.
  • Problem Solving: Excellent analytical and debugging skills for complex distributed systems.
  • Communication: Ability to explain complex technical issues to scientists and non-technical stakeholders.
  • Experience: Hands-on experience in data centers, managing large clusters, and supporting diverse scientific/AI workloads

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