Role Title: Engineering Intelligence Lead – Jellyfish / Delivery Observability
Role Summary
Own the implementation and operation of engineering intelligence and delivery observability using Jellyfish. 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.
Key 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
* Delivery bottlenecks and inefficiencies
* Integrate Jellyfish with tools such as:
* Azure DevOps (ADO)
* GitHub
* Jira (future target)
* Design dashboards and reporting for:
* Leadership visibility
* Delivery governance
* Collaborate with:
* AI DLC teams
* App Ops / Observability teams
* Enable data-driven decision making for engineering leadership
* Support scaling of the tooling ecosystem as additional tools are onboarded
Required Skills
* Strong experience with Jellyfish or similar engineering intelligence platforms
* Experience with SDLC tools integration
* GitHub
* ADO
* Jira
* Understanding of:
* Agile delivery metrics
* Software engineering lifecycle
* Experience building reporting dashboards and analytics frameworks
* Strong stakeholder management skills
Preferred Skills
* Exposure to AI/ML development lifecycle (AI DLC)
* Experience in observability and app performance measurement
* Familiarity with engineering productivity metrics frameworks
Profile Expectation (Critical per Sufian)
* Hands-on and immediately deployable
* Capable of working directly with product and engineering teams
* Able to operate in high-pressure, fast-moving environments
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