About The Position

Own the Jellyfish platform, implementation and operation of engineering intelligence and delivery observability. The role will enable visibility into delivery lifecycle performance, engineering productivity, and workflow efficiency across AI initiatives. This role is expected to immediately take over tooling ownership and partner with product, engineering, and AI teams to operationalize insights.

Requirements

  • Strong experience with Jellyfish or similar engineering intelligence platforms
  • Experience with SDLC tools integration (GitHub, ADO, Jira)
  • Understanding of Agile delivery metrics
  • Understanding of Software engineering lifecycle
  • Experience building reporting dashboards and analytics frameworks
  • Strong stakeholder management skills
  • 6-8 years of experience
  • Hands-on and immediately deployable
  • Capable of working directly with product and engineering teams
  • Able to operate in high-pressure, fast-moving environments

Nice To Haves

  • Exposure to AI/ML development lifecycle (AI DLC)
  • Experience in observability and app performance measurement
  • Familiarity with engineering productivity metrics frameworks
  • Microsoft Azure
  • Github Enterprise

Responsibilities

  • Lead onboarding, configuration, and operationalization of Jellyfish platform
  • Provide end-to-end visibility into delivery lifecycle and work orchestration
  • Enable tracking of engineering productivity, work throughput and cycle time, and delivery bottlenecks and inefficiencies
  • Integrate Jellyfish with tools such as Azure DevOps (ADO), GitHub, Jira (future target)
  • Design dashboards and reporting for leadership visibility and delivery governance
  • Collaborate with AI DLC (Delivery lifecycle) teams and App Ops / Observability teams
  • Enable data-driven decision making for engineering leadership
  • Support scaling of the tooling ecosystem as additional tools are onboarded
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