Sr Manager, Lead Delivery Leader
About the role
The role of Delivery Leader at Deloitte involves orchestrating execution across multiple product teams, service lines, and enterprise functions. This includes holding the cross-team view necessary for effective coordination and managing dependencies across products and platforms.
Responsibilities
Lead large-scale, AI-native implementations ensuring each program delivers the outcome its charter promised, right-sizing program structures to scale, and partnering with Product, Engineering, Architecture, and Experience leaders to hold the strategic line.
Evangelize product engineering models, actively experimenting with GenAI to keep delivery practices current.
Drive evidence-gated delivery, defining standards, evaluation criteria, and exception handling for AI agents participating in delivery, using telemetry and audit trails for quality and KPI tracking.
Coach and calibrate Delivery Managers, building their fluency in AI-native discovery and delivery methodologies and growing the Delivery community of practice.
Run alignment cadence at the level the work demands, embedding continuous, evidence-backed governance in the pipeline (policy as code, telemetry, immutable audit trails) rather than periodic gates, carrying programs through operation with durable accountability.
Anchor teams to the charter outcome, treating "deployed evidence confirms intended behavior" as the real definition of done, and carry initiatives into adoption so value lands in the customer's hands.
Keep the engineering model lean by governing intake of AI-generated artifacts so they become productive inputs rather than noise, defining how AI agents operate in workflows, and using evidence gates to cut work that isn't earning its place.
Reconcile conflicting stakeholder and AI-drafted artifacts on the same initiative, run forums where alignment happens, and escalate deliberately—surfacing trade-offs and holding the room until a decision is made.
Manage dependencies across products and platforms using evidence-gated cycles, continuous governance, and audit trails as primary risk controls to surface issues early and decide contingencies before they become incidents.
Engage stakeholders across Product, Experience, and Engineering, govern AI-generated artifact intake as a partnership, and model senior Delivery behaviors: judgment under uncertainty, stakeholder steadiness, and evidence orientation.
Requirements
Experience: 15+ years of progressive delivery leadership experience in product engineering, enterprise technology, or management consulting environments.
Demonstrated track record leading large, cross-functional programs - defined as programs with multiple product teams, multiple stakeholders, and meaningful cross-function dependencies.
Direct experience with both Agile/Lean operating models and the emerging intent-driven, evidence-gated delivery patterns.
Strong expertise in AI/Cloud FinOps, budget management, financial forecasting, vendor management, cost optimization, and data-driven delivery governance.
Prior experience coaching Delivery Managers or Program Managers.
Ability to travel 10% on average based on the work you do and the clients and industries/sectors you serve.
Limited immigration sponsorship may be available.
Qualifications
Engineering fluency: Comfortable in technical conversations with architects and senior engineers; able to challenge feasibility claims and reason about trade-offs without needing translation.
Stakeholder orchestration at scale: Track record of holding alignment across senior internal stakeholders with competing priorities.
AI-augmented working practice: Fluent with current GenAI assistants and agentic delivery tooling. Able to direct AI output and design where AI agents fit in delivery workflows and where humans must remain in the loop.
Communication: Exhibit excellent communication skills to inspire and influence stakeholders. Serve as the contact for value achievement and collaborate with product engineering teams. Facilitate co-creation workshops to foster alignment and decision-making.