AI Scrum master

We are seeking an AI Scrum Master with 5+ years of experience in IT and digital product delivery. You will act as the scrum leader and delivery coach for cross-functional teams, owning the health of the Agile process, removing impediments, and enabling teams to deliver predictable, high-quality outcomes. The role requires strong facilitation, coaching, and delivery management skills in Agile environments, combined with hands‑on use of AI to make teams faster and more focused.

As we grow into an AI-native way of working, we want someone who is already using LLMs and AI tools in their daily work and is genuinely curious about how these tools can reshape team ceremonies, delivery tracking, and the way engineering teams collaborate.

Key Responsibilities

Agile Delivery Leadership

• Facilitate all Scrum ceremonies: sprint planning, daily stand‑ups, backlog refinement, sprint reviews, and retrospectives.
• Own the team's delivery cadence across the full SDLC, from discovery and refinement through build, test, release, and post‑release support.
• Track sprint and release progress, flag risks early, and keep delivery commitments realistic and transparent.
• Proactively identify, escalate, and remove impediments that block team progress.
• Manage cross‑team dependencies and coordinate with other Scrum Masters, Product Owners, and delivery leads on shared releases.
• Ensure a clear and consistent Definition of Ready and Definition of Done across teams.
• Use LLM tools to accelerate ceremony preparation, sprint summaries, status reports, and retrospective synthesis, while maintaining accuracy and team trust.

Backlog & Flow Management

• Partner with the Product Manager/Owner to keep the backlog healthy, prioritized, and refined at least two sprints ahead.
• Help teams break down epics and features into well‑sized, testable user stories with clear acceptance criteria.
• Monitor flow metrics such as velocity, cycle time, throughput, and work in progress, and use them to drive improvement.
• Make bottlenecks, scope changes, and carry‑over visible to the team and stakeholders.
• Collaborate with QA and development teams to ensure work meets quality standards before it is considered done.
• Apply AI‑assisted analysis to Jira data, sprint history, and retrospective notes to surface patterns, risks, and improvement opportunities.

Team Coaching & Continuous Improvement

• Coach team members, Product Owners, and stakeholders on Agile principles, Scrum practices, and self‑organization.
• Foster a culture of psychological safety, accountability, and continuous improvement.
• Run retrospectives that lead to concrete, tracked improvement actions rather than repeated discussions.
• Assess team and organizational Agile maturity and tailor coaching to the team's context.
• Help teams adopt AI‑native ways of working, including practical use of LLMs and AI agents in planning, documentation, testing, and delivery.
• Stay current on LLM and AI agent capabilities and understand where they can be practically applied within the delivery process.

Adaptability & Strategic Thinking

• Quickly assess IT environments, delivery models, and organizational maturity.
• Adapt Agile practices to Scrum, Kanban, or hybrid delivery approaches as the engagement requires.
• Think strategically about delivery predictability while remaining hands‑on in day‑to‑day team execution.
• Navigate ambiguity, changing priorities, and evolving technical constraints.
• Provide input to release planning, capacity planning, and roadmap feasibility.

Stakeholder Engagement & Collaboration

• Act as a trusted partner to business stakeholders, client leadership, and IT leadership on delivery matters.
• Facilitate complex discussions, workshops, and PI or quarterly planning sessions with senior and technical stakeholders.
• Bridge communication between business, product, and engineering teams.
• Provide clear, honest reporting on progress, risks, and delivery health throughout the SDLC.
• Manage stakeholder expectations and shield the team from unplanned disruption.

Delivery Health & Metrics

• Define and maintain team‑level delivery metrics and dashboards that show predictability, quality, and flow.
• Use data to drive conversations about capacity, commitments, and process changes.
• Coach and mentor junior Scrum Masters and team members in Agile and delivery practices.
• Contribute to defining how AI adoption is measured within teams, including time saved, output quality, and team confidence in AI‑assisted work, not just tool usage numbers.