Cornelis Networks, Inc.

Cornelis Networks, Inc.

Engineering Tools Administrator

Wayne, Pennsylvania · Senior · Full-time

Sponsorship not specifiedDetected 16 hours ago
PythonBashGitAWSAnsibleLinuxDevOpsJiraConfluenceHardware DesignCommunicationCompTIA

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Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

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About the role

  • Our differentiated architecture integrates hardware, software, and system-level technologies to maximize the efficiency of GPU, CPU, and accelerator-based compute clusters at scale.
  • As a global organization, our team spans multiple U.S. states and six countries, and we continue to expand with exceptional talent in onsite, hybrid, and remote roles.
  • Cornelis Networks is seeking an Engineering Tools Administrator to serve as the day-to-day administrator for developer tools and lab systems used by our software engineering organization.

Responsibilities

  • Configure and maintain approved organization- and repository-level permissions, team hierarchies, and role-based access control.
  • Maintain branch protection rulesets, repository templates, and repo lifecycle policies.
  • Develop, m aintain and troubleshoot tool integrations and webhooks.
  • Configure and maintain Jira projects, workflows, permission and notification schemes, custom fields, and screens to match engineering and program management needs.
  • Configure and maintain our Confluence universe.
  • Manage SSH and user access and bridge the gap between the IT organization and the engineering team for our development and test infrastructure. Maintain an accurate inventory of lab assets and access across people and automations.
  • Perform routine AWS administration supporting engineering, including IAM access changes, EC2 lifecycle operations, S3 access configuration, tagging, and cost and usage review.
  • Partner Across Program Management, Engineering Management, and DevOps
  • Partner with program management on Jira configuration and release reporting, with engineering management on implementing approved access and governance controls, and with the DevOps team on infrastructure standards, escalations, and changes outside this role's administrative scope.
  • Provide Frontline Developer Support and Documentation

Requirements

  • Previous experience administering these tools through software and/or hardware engineering releases.
  • Working knowledge of Linux system administration (RHEL, Rocky Linux, or Ubuntu).
  • AWS certification is not required.
  • Basic scripting or automation experience (e.g., Bash, Python) for repetitive administrative tasks.
  • Bachelor's degree in Computer Science, Engineering, Information Technology, or equivalent practical experience.
  • Strong written and verbal communication skills, with the ability to work across program management, engineering management, and DevOps.

Nice to have

  • Current GitHub Administration or Atlassian administration certification, such as GH-100, ACP-120, or a successor credential, is helpful but not required.
  • Red Hat Certified System Administrator (RHCSA), CompTIA Linux+, or LPIC-1.
  • Experience in a hardware, semiconductor, or networking engineering environment, including familiarity with lab equipment such as PCIe test cards and out-of-band management tools (IPMI, BMC).
  • Infrastructure-as-code experience (e.g., Ansible, SaltStack ) for provisioning lab or test systems.
  • Experience with identity federation (SSO/SAML/SCIM) via providers such as Okta, Entra ID, or FreeIPA.
  • Cornelis Networks does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services.
  • We encourage applications from all qualified candidates and will accommodate applicants' needs under the respective laws throughout all stages of the recruitment and selection process.

Compensation

  • We offer a competitive compensation package that includes equity, cash, and incentives, along with health and retirement benefits.

Company info

  • Our solutions help customers push the boundaries of AI and HPC by eliminating bottlenecks and enabling massive-scale training, inference, simulation, and data-intensive workloads.
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