Roles and Responsibilities:
Work Mode: Hybrid
Role Overview
We are looking for an experienced Agile Scrum Master to facilitate delivery across one or more AI-first, cross-functional pods. The role sits at the intersection of agile coaching, delivery orchestration, and AI-augmented engineering. You will work closely with Python developers, full stack engineers, QA specialists, and AI/ML practitioners to ensure pods deliver high-quality software in fast-paced, time-boxed sprints.
Beyond traditional scrum facilitation, this role requires a working understanding of Agentic AI delivery contexts — including human-in-the-loop (HITL) workflows, AI-assisted sprint tooling, and the dynamics of integrating LLM-based capabilities into production systems. You are as comfortable removing blockers on an API integration sprint as you are coaching the team on first-time-right engineering discipline and retrospective effectiveness.
Key Responsibilities
Scrum Facilitation and Ceremony Ownership
Own and facilitate all Scrum ceremonies: sprint planning, daily standups, sprint reviews, retrospectives, and backlog refinement sessions.
Ensure ceremonies are purposeful, time-boxed, and result in clear actions and commitments from the team.
Maintain sprint cadence and protect the team from mid-sprint scope changes, context switching, and external disruptions.
Track sprint velocity, capacity, and completion trends; use data to improve planning accuracy over successive sprints.
Produce clear sprint reports and delivery status summaries for internal stakeholders and delivery leadership.
AI-First Pod Delivery Support
Facilitate delivery within pods building Agentic AI platforms — including LLM integration, RAG pipelines, agent orchestration, and API-first backend services.
Understand the unique delivery dynamics of AI development: non-deterministic outputs, prompt iteration cycles, HITL evaluation loops, and model evaluation gates.
Help the team schedule and time-box HITL review tasks — including human evaluation of AI agent outputs — within sprint plans, ensuring they are treated as first-class delivery items.
Bridge communication between AI/ML engineers, backend developers, QA, and product owners, ensuring alignment on what 'done' means for AI-integrated features.
Support the team in defining acceptance criteria for AI-generated outputs, including quality thresholds, confidence scores, and fallback handling.
Impediment Removal and Dependency Management
Proactively identify, track, and resolve blockers — whether technical, organisational, or cross-team — before they impact sprint commitments.
Maintain a visible impediment log and escalate unresolved blockers to delivery heads or programme leads with context and recommended actions.
Manage cross-pod and cross-functional dependencies, coordinating with other scrum masters, tech leads, and platform teams as needed.
Facilitate alignment between integration-heavy workstreams — internal system integrations, external API onboarding, and third-party SaaS dependencies.
Agile Coaching and Team Development
Coach pod members — including developers, QA, and leads — on Agile principles, Scrum practices, and continuous improvement habits.
Foster a culture of psychological safety, honest retrospectives, and blameless post-mortems within the pod.
Encourage first-time-right engineering discipline: help the team invest in definition of ready, clear acceptance criteria, and upfront design discussions before coding begins.
Guide the team in adopting good engineering hygiene: unit testing, code reviews, refactoring cycles, and technical debt management as sprint-level practices.
Support onboarding of new pod members and help them integrate quickly into team norms and delivery rhythm.
Metrics, Reporting, and Continuous Improvement
Define and track key delivery metrics: sprint velocity, cycle time, defect escape rate, HITL evaluation throughput, and sprint goal achievement rate.
Produce concise sprint and delivery health dashboards for internal stakeholders, adapting format and depth to the audience.
Run structured retrospectives using proven formats (Start/Stop/Continue, 4Ls, fishbone) and ensure retrospective actions are tracked and closed.
Continuously evaluate and improve team ways of working — including tooling, ceremonies, and integration with AI-assisted development workflows.
Contribute to centre-of-excellence or community-of-practice initiatives across scrum masters in the organisation.
Stakeholder Communication and Governance
Serve as the primary delivery communication point between the pod and internal stakeholders, product owners, and programme leads.
Provide timely, transparent updates on sprint progress, risks, and delivery confidence — including any AI evaluation or integration risks.
Support programme-level planning activities including PI planning, roadmap reviews, and quarterly delivery forecasts.
Maintain JIRA, Azure DevOps, or equivalent tools: board hygiene, story status accuracy, burndown charts, and sprint closure.
Required Skills and Qualifications
Agile and Scrum Expertise
7+ years of experience as a Scrum Master or Agile Delivery Lead in software product or platform delivery teams.
Deep working knowledge of Scrum framework; familiarity with Kanban, SAFe, or LeSS is an advantage.
Certified Scrum Master (CSM, PSM I/II) required; Advanced certifications (A-CSM, PSM III, SAFe SM) are a strong plus.
Proven track record of facilitating cross-functional pods with developers, QA, and product roles in fast-paced sprint environments.
Strong command of delivery metrics: velocity, cycle time, sprint burn-down, and escaped defects.
AI-First Delivery Context
Working understanding of how AI and LLM-based development differs from conventional software delivery — including iterative prompt development, non-deterministic output handling, and HITL evaluation workflows.
Ability to facilitate sprint planning and review ceremonies for AI-integrated features with appropriate acceptance criteria.
Familiarity with Agentic AI concepts — agent orchestration, RAG pipelines, tool-use workflows — sufficient to facilitate delivery discussions without deep technical hands-on involvement.
Experience supporting teams integrating internal and external APIs or third-party platforms within sprints.
Tooling and Processes
Proficient with JIRA, Azure DevOps, or equivalent project and sprint management tools — including board configuration, reporting, and hygiene practices.
Comfortable with Confluence, Notion, or similar documentation platforms for sprint artefacts and team wikis.
Familiarity with CI/CD concepts and basic DevOps delivery pipelines to facilitate informed sprint conversations with engineering teams.
Experience with remote or distributed team facilitation tools (Miro, FigJam, Retrium, or equivalent).
Interpersonal and Communication Skills
Excellent facilitation skills — able to drive focused, outcome-oriented conversations with diverse, opinionated technical teams.
Clear and concise communicator across all levels: engineers, product owners, delivery managers, and senior stakeholders.
Skilled at conflict resolution, managing team dynamics, and maintaining team momentum through uncertainty.
Able to distinguish between coaching, mentoring, facilitating, and directing — and apply each at the right moment.
Nice to Have
Experience as a Scrum Master within an offshore or distributed delivery model across multiple time zones.
Background in or exposure to regulated industry domains such as pharma, fintech, or healthcare.
Basic technical literacy in Python or full stack development — enough to understand story complexity and engineering tradeoffs.
Exposure to AI-assisted project management or sprint tooling (AI-generated summaries, sprint risk detection, etc.).
Experience supporting presales or proposal activities with delivery approach documentation.
Knowledge of programme-level delivery frameworks: SAFe, LeSS, or Spotify model.
What We Offer
A high-impact role at the centre of AI-first engineering delivery, working with modern Agentic AI technology stacks.
Collaboration with experienced delivery leads, architects, and AI practitioners in a fast-moving, learning-oriented culture.
