Manager, Delivery Manager

About the role

The role involves program-level coordination for significant initiatives or sets of related programs, ensuring that dashboards start when slices are ready and end when deployed evidence confirms the intended behavior has shifted.

Responsibilities

• Own program-level coordination for one significant initiative or a set of related programs.
• Ensure dashboards start when slices are ready and end when deployed evidence confirms the intended behavior shifted.
• Day-to-day stakeholder orchestration with internal Deloitte stakeholders at the program level, including reconciliation of AI-drafted artifacts when stakeholders arrive with their own briefs.
• Drive cost-efficient adoption of LLM, agentic AI, and cloud platforms through effective governance, FinOps practices, and consumption optimization.
• Operational integrity of the evidence-gated cycle in your scope: proof signals being read, harm watches honored, and exit gates respected before slices expand.

Qualifications

• 10+ years of delivery management with direct experience leading a cross-functional program or set of programs with meaningful dependencies and multiple stakeholders.
• Experience operating inside an Agile or Lean model and demonstrated readiness to operate inside intent-driven, evidence-gated delivery patterns.
• Experience working in a product-staffed model where durable product teams stay with their products across build, deploy, operate, and evolve.
• Strong expertise in AI/Cloud FinOps, budget management, financial forecasting, vendor management, cost optimization, and data-driven delivery governance.
• 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.

Required Skills

• Coordination at scale: track record of managing dependencies, surfacing risks, and driving alignment across teams that do not naturally talk to each other.
• Engineering fluency: able to follow technical conversations, ask useful questions, and challenge feasibility claims constructively (more than passive listening).
• Evidence orientation: comfortable measuring delivery by outcome validation rather than velocity proxies. Able to hold the line on evidence gates.
• AI-augmented working practice: fluent with current GenAI assistants and agentic delivery tooling. Able to direct AI output for status, risk, and coordination tasks rather than only consume or produce it manually.
• Specification literacy: able to read and reason about charter, persona, intent, constitution, and blueprint artifacts and understand how a program is governed through them.
• Communication: writes clearly. Presents to senior stakeholders without over formatting. Tells the truth about status, including bad news, without varnish.