JD Jellyfish (Engineering Intelligence Observability Lead)
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:
o Engineering productivity
o Work throughput and cycle time
o Delivery bottlenecks and inefficiencies
Integrate Jellyfish with tools such as:
o Azure DevOps (ADO), GitHub, Jira (future target)
Design dashboards and reporting for:
o Leadership visibility
o Delivery governance
Collaborate with:
o AI DLC teams
o 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:
o Agile delivery metrics
o Software engineering lifecycle
Experience building reporting dashboards and analytics frameworks
Strong stakeholder management skills
Preferred Skills
Exposure to AIML development lifecycle (AI DLC)
Experience in observability and app performance measurement
Familiarity with engineering productivity metrics frameworks
Profile Expectation (Critical per Customer)
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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Role Descriptions: Lead onboarding configuration and operationalization of Jellyfish platformProvide end-to-end visibility into delivery lifecycle and work orchestrationEnable tracking of:oEngineering productivityoWork throughput and cycle timeoDelivery bottlenecks and inefficiencies [TCS Discus...ng and SoW Meeting]Integrate Jellyfish with tools such as:oAzure DevOps (ADO) GitHub Jira (future target) [TCS Discus...ng and SoW Meeting]Design dashboards and reporting for:oLeadership visibilityoDelivery governanceCollaborate with:oAI DLC teamsoApp Ops Observability teamsEnable data-driven decision making for engineering leadershipSupport scaling of the tooling ecosystem as additional tools are onboarded
Essential Skills: Engineering Intelligence Lead Jellyfish Delivery Observability
Desirable Skills:
Keyword:
Skills: AI for Leadership
Experience Required: 10 & Above
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