Portfolio Lead

The Portfolio Lead is accountable for delivery performance across a sub-domain of 4-6 pods (Engineering, Quality, Product). They lead the flow of value from idea to production, ensuring pods deliver with pace, predictability and understanding of outcomes. They combine hands-on delivery leadership with AI-augmented ways of working and data-driven decision-making. They do not prescribe a single framework - instead, they adapt approaches that best serve each pod's context. They partner with Engineering and Product leadership to reduce waste, improve throughput and help pods achieve Autonomy, Accountability and Agreement to value outcomes.

The candidate will have responsibilities across the following functions:

Pod Performance and Accountability:

• You are responsible for pod delivery performance across the sub-domain.
• You will lead and communicate delivery health, risks and performance to leadership.
• Ensure pods operate as self-organising units delivering value outcomes.
• Support pod leads with coaching, facilitation and conflict resolution.
• Ensure cross-pod agreement on priorities, dependencies and shared goals.
• Facilitate communication and collaboration between pods to promote knowledge sharing.

Problem Solving:

• You will be an expert; deploy root cause analysis, systems thinking and structured techniques to analyse and guide out resolutions.
• Be an escalation point for cross-pod blockers and systemic impediments.
• Identify patterns across pods that indicate deeper organisational or process issues.

AI-Augmented Delivery:

• Champion AI agent adoption across pods - including coding agents, test generation, story creation, board health and deployment automation.
• Identify opportunities where AI can reduce toil, accelerate delivery or improve decision-making.
• Apply AI to improve delivery effectiveness, including workflow insights, risk prediction, and automation of reporting.
• Track and demonstrate the impact of AI on delivery performance.

Flow and Efficiency:

• Monitor and improve delivery flow (lead time, cycle time, WIP, throughput) using Kanban and lean principles.
• Ensure WIP limits are respected and surface ageing items through Board Walks.
• Identify bottlenecks, ageing work and sources of delay across pods.
• Improve through regular assessment and experimentation.
• Support teams in breaking down work into deliverable, value-driven increments.

Agile Ways of Working:

• Support and evolve the agile operating model for a pod-based environment focused on pace, not ceremony.
• Adapt delivery approaches (Kanban, flow-based, lean) appropriate to each pod's needs.
• Ensure consistency of practice across pods without being prescriptive.
• Promote outcome-driven delivery vs. output-driven activity.
• Guide teams to operate with autonomy and accountability.

Metrics and Reporting:

• Define and maintain delivery metrics: cycle time, flow efficiency, lead time of initiative, PDLC compression, dependency reduction, rework rate, team satisfaction, and AI effectiveness.
• Build dashboards (cumulative flow diagrams, throughput charts, WIP ageing) that provide leadership visibility and lead informed decision-making.
• Analyse performance data to identify trends, patterns and areas for improvement.
• Use data to facilitate conversations and coach pods — not just track output.

Stakeholder Management:

• Partner with Engineering and Product leadership at sub-domain level.
• Represent delivery health and risks in leadership forums.
• Build trusted relationships that allow fast decision-making.
• Communicate delivery performance to both technical and non-technical audiences.

Commercial Awareness:

• Understand the commercial context of the sub-domain.
• Connect delivery decisions to revenue, cost, and customer impact.
• Support prioritisation trade-offs with a business lens.

Capacity Planning:

• Forecast capacity across pods based on team composition, skills mix and upcoming demand.
• Identify resourcing gaps and support hiring/allocation decisions.
• Balance workload across pods to prevent burnout and underutilisation.
• Support realistic planning by ensuring pods have a clear understanding of available capacity.

Risk and Dependency Management:

• Manage risks through regular assessment and execution of controls.
• Ensure cross-pod dependencies are visible, tracked and managed.
• Track dependency cost (time blocked, items affected) and lead mitigations such as contract-first development and feature flags.
• Support issue escalations, ensuring intervention by the dependency escalation protocol.

Coach and Capability Development:

• Provide hands-on coaching at pod level.
• Build capability in workflow management, flow thinking, estimation, planning, and data-led decision-making.
• Support teams in understanding and improving their own performance.
• Strengthen a culture of continuous improvement and learning.

Outcome and Value Focus:

• Align delivery to always ensure outcomes and value.
• Help teams understand the why behind their work and how their outputs contribute to value.
• Challenge work that does not link to outcomes.
• Support measurement of delivery against OKRs and value indicators.

Centre of Excellence (CoE) Contribution:

• Be an active contributor to the CoE.
• Share best practices, delivery insights and improvement opportunities from pods.
• Support adoption of standards, playbooks and tools.
• Help evolve delivery practices based on experience.

Requirements:

• You will have 7+ years in delivery/agile roles, with at least 3 years operating across multiple teams simultaneously in a technology environment.
• Expert in flow-based delivery approaches (Kanban, lean, continuous delivery) — not limited to Scrum.
• Experience enabling multiple teams/pods simultaneously at scale.
• Strong understanding of AI tooling and its application to software delivery (coding assistants, automation, intelligent analytics).
• Experienced in capacity planning, demand forecasting and resource optimisation across multiple teams.
• Use data to solve complex problems; can interpret and communicate complex data sets clearly.
• Previous experience of organisational transformation and change management.
• Good knowledge of Objectives and Key Results (OKR) strategy.
• Experience in a regulated industry (gaming, fintech, or similar) desirable.