Delivery Manager, AI products

Product Engineering Organization

Overview

As a Delivery Manager, you hold program-level execution accountable on a day-to-day basis within Deloitte's Product Engineering organization, one or more product teams operating against a shared set of intents.

Delivery in this organization operates inside an intent-driven development model with three concurrent layers — governance, execution, and learning — that run simultaneously. Execution advances in evidence-gated dashes, not sprints.

The activities that used to define this role — status compilation, schedule maintenance, risk-log upkeep, and ceremony documentation — are increasingly AI-assisted. What remains, and grows, is the judgment work: cross-team coordination on initiatives larger than a single product team can self-coordinate, stakeholder alignment, dependency management, and the operational discipline that keeps evidence-gated delivery.

Work you'll do:

• Program-level coordination for one significant initiative or a set of related programs. Ensure dashes 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.

Core Responsibilities

• Outcome-Driven Leadership: Deliver the right customer and business outcomes by engaging product teams on structure, skills, leverage models, and measurement. Scope dashes against ready slices and observable evidence, so work advances when deployed evidence confirms the behavior shifted — not at a sprint boundary.
• Delivery Leadership and Advocacy: Champion fit-for-context delivery methodologies and work with Product Managers to drive priorities and execution. Form skilled teams, remove roadblocks, and set cadence to the rhythm the program needs. Surface coordination friction before it becomes a blocker, escalating to the Delivery Leader when it exceeds your authority.
• Craft Mastery: Foster delivery excellence through quality processes, program value delivery, and team growth — coaching junior professionals via pairing, observation, and feedback. Experiment with new tools like GenAI and support the AI Workflow Orchestrator on your program, knowing which workflows are AI-driven and how exceptions route. Spread knowledge through community sessions.
• Communication: Inspire and influence stakeholders, serving as the contact for value achievement across product engineering teams. Communicate status accurately on the cadence the program needs. Hold the room when stakeholders disagree: surface trade-offs, recommend a path, drive to decision. Facilitate co-creation workshops.
• Cross-Functional Collaboration: Work as a connected member of the program alongside the triad ensemble (Product, Engineering and Experience) and cross functional groups. Maintain a live picture of dependencies across the product teams and platform services you touch. Manage conflict, foster collaboration, and enable cross-skilling.
• Discovery & Delivery Proficiency: Apply deep SDLC expertise with continuous planning and refinement. Watch for drift between intent and execution and raise it early. Hold evidence-gate discipline — proof signals read, harm watches honored, exits and expansions respected. Identify risks, adapt scope, and embed continuous improvement.
• Customer-Centric Delivery: Drive lean solutions through rapid experimentation, engaging customers before, during, and after delivery to land the right solution effectively.
• Operational Excellence: Build inclusive, engaged teams; remove obstacles and coach; improve satisfaction and reduce attrition. Govern the intake of AI-drafted artifacts so they become productive inputs, not noise. Report on financials, innovation, and engagement, and drive efficiency and productivity.
• Engagement and Collaborative Co-Creation: Engage stakeholders at all levels and foster a culture of co-creation. Hold the relationship with program sponsors and affected stakeholders, informing them in proportion to their stake, and reconcile conflicting AI-generated artifacts on the same initiative. Align diverse perspectives to deliver quality solutions.
• Domain Expertise: Rapidly acquire domain-specific knowledge and navigate enterprise functions to drive product value and organizational alignment.

The Team

US Deloitte Technology Product Engineering has modernized software and product delivery, creating a scalable, cost-effective model that focuses on value and outcomes. It leverages a progressive and responsive talent structure across a four-capability matrix: Product, Experience, Engineering, and Delivery. As Deloitte's primary product development team, Product Engineering delivers innovative digital solutions to businesses, service lines, and internal operations with proven bottom-line results. We develop and deploy cutting-edge go-to-market solutions that help Deloitte operate effectively and lead in the market.

Qualifications

Required Experience

• 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.
• Candidates must be located within a commutable distance to one of the select locations available for this role 
• Ability to work in your local office at a minimum of 3 days per week

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.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $107,700 to $221,200.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

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