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Scrum Master Lead

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Hybrid

Scrum Master Lead

Ascendion Engineering

Scrum Master Lead

Skills

Product StrategyAIJiraConfluenceSupply Chain

1 month ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Hybrid

Published on:

14 October 2026

What they need


Job highlights

  • 10+ years experience with AI domain literacy in Generative AI, LLMs, and expert Jira Cloud and Confluence skills
  • Own and prioritize Merlin product roadmap, translate business problems into technical specs, facilitate agile ceremonies, and coordinate knowledge transfer

Job Description

Scrum Master cum Business Analyst cum Product Owner

Role Summary:

10+ years of experience

A highly versatile, multi-disciplinary leadership role designed to orchestrate the end-to-end lifecycle of the Merlin AI product line. This position functions as a functional translator, bridging the gap between Schreibers business units (Supply Chain, Commercial, Risk) and the technical AI engineering team, while simultaneously running agile delivery cadences.

Key Responsibilities:

  • Product Ownership (PO): Own, prioritize, and ruthlessly groom the Merlin product roadmap and Q4 use-case backlogs in strict collaboration with digital business sponsors.
  • Business Analysis (BA): Elicit complex business problems and translate them into clear, technical requirement specifications, User Stories, and explicit Acceptance Criteria (Given/When/Then) in Jira.
  • Scrum Master (SM): Facilitate standard agile ceremonies (Daily Stand-ups, Sprint Planning, Backlog Refinement, Retrospectives), remove engineering blockers, and protect the team's sprint velocity and commitment predictability.
  • Knowledge Transfer Coordination: Lead the execution of the Merlin Transition Playbook. Coordinate the formal codebase reviews, documentation centralization, and shadow support timelines to smoothly transition knowledge from the outgoing vendor.

Must-Have Professional Skills:

  • AI Domain Literacy: Conceptual understanding of Generative AI principles, Large Language Models (LLMs), tokenization, and vector data storage to effectively evaluate AI use-case feasibility.
  • Agile Tooling Mastery: Expert-level proficiency in Jira Cloud and Confluence for project configuration, sprint monitoring, and knowledge asset mapping.
  • Soft Skills: Master-level executive presence, conflict resolution, and change-management capabilities to navigate complex, cross-functional stakeholder landscapes.

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