PnP Pipeline On-call Support Engineer

14 hours, 19 minutes ago
Mid Level
DevOps and Infrastructure
PHIZENIX

PHIZENIX

PHIZENIX is a Silicon Valley-based talent solutions company that specializes in AI consulting services, tech talent acquisition, and AI workforce training. The company aims to empower organizations by connecting them with exceptional talent and consulting solutions, enabling AI to work alongside people. With a team of tech founders and operators, PHIZENIX offers comprehensive support for businesses on their AI transformation journey. Their services include designing and implementing AI solutions, connecting companies with skilled technology professionals, and providing training programs to enhance workforce capabilities. The company focuses on cultural fit in talent deployment and offers corporate training to help teams integrate AI into their daily operations. PHIZENIX primarily serves businesses looking to hire top talent, deploy AI, transform workflows, and train employees in using AI tools effectively. The company has approximately 50–100 employees and has received support from investors like i3 Ventures.

information technology & services
11-50
Founded 2025

Description

  • Conduct proactive health checks on functional and PnP-enabled pipelines.
  • Verify that test results are populating correctly on the RLS PnP dashboard.
  • Investigate pipeline failures and classify them as infrastructure, UTF/PnP analyzer, or mature pipeline issues.
  • Perform straightforward bug fixes for deployment or execution changes.
  • Escalate infrastructure issues through the appropriate internal channels.
  • Escalate complex or systemic issues to pipeline owners with relevant logs and context.
  • Collaborate with pipeline owners and XFN DRIs on PnP trace tag placement and measurement window alignment.
  • Reduce manual overhead for engineering teams by serving as the first line of defense for pipeline issues.

Requirements

  • Proven experience monitoring alerts and dashboards.
  • Strong troubleshooting skills with the ability to identify patterns in failure logs and suggest improvements.
  • Ability to distinguish between infrastructure, firmware, and analyzer-specific errors.
  • Familiarity with jest-e2e and the Unified Test Framework (UTF) is preferred.
  • Experience working within internal infrastructure such as buck, sandcastle, phabricator, or internal AI tooling is preferred.
  • Ability to read and interpret CI pipeline logs effectively is preferred.
  • Ability to leverage AI tooling effectively, such as Claude Code or Metamate, is preferred.

Interested in this position?

Apply directly on the company website

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