Physical AI Delivery Manager

We are:

Accenture helps the world's leading enterprises reinvent by building their digital core and unleashing the power of AI to create value at speed for organizations across industries. Our strategy is to be the reinvention partner of choice for our clients and lead in the safe, widespread adoption of AI, and to be the most client-focused, AI-enabled, great place to work in the world.

We bring together the talent of our approximately 799,000 people with proprietary assets and platforms, deep process and industry expertise, and leading ecosystem relationships to deliver end-to-end solutions and measurable outcomes ough our Reinvention Services, we offer broad expertise across Cybersecurity, Digital Core, Finance, Industry and Enterprise, Song, Supply Chain and Engineering, and Talent, with advanced capabilities in AI and Data, Industry and Process, and Technology.

We serve approximately 9,000 clients and generated approximately $70 billion in FY25 revenue. Visit us at

About the Physical AI Team:

Accenture combines strategy, digital twins and simulation, robotics intelligence, orchestration, industrial integration and managed operations to help clients scale autonomous and adaptive physical operations. Delivery requires technical credibility, industry understanding, consulting discipline and rigorous controls for production deployment.

The Work:

The Physical AI Delivery and Solutioning Manager leads client work streams and small-to-medium Physical AI engagements from discovery and solution definition through mobilization, implementation, validation and transition. The role combines delivery accountability with sufficient technical depth to guide engineering decisions, enough industry understanding to redesign operating workflows, and the consulting capability to manage stakeholders, value, scope, risk and team performance.

Key Responsibilities

+ Lead delivery work streams across digital twins and simulation, robotics AI and training, robotic orchestration, industrial integration or related Physical AI domains.

+ Own workplans, milestones, staffing, budget, quality, dependencies, risks, decisions and client communications for the assigned scope.

+ Translate operational problems into requirements, use cases, target outcomes, delivery increments, acceptance criteria and value-realization measures.

+ Contribute to solution design, estimates, staffing models, implementation roadmaps, proposals, statements of work and delivery mobilization.

+ Coordinate engineers, architects, industry SMEs, data and AI teams, cloud and edge teams, OT specialists, cybersecurity teams and ecosystem partners.

+ Provide design and delivery governance across architecture decisions, interfaces, testing, safety, OT security, responsible AI, human-in-the-loop controls and production readiness.

+ Guide teams through simulation, integration, hardware-in-the-loop, user acceptance, site acceptance, commissioning and transition-to-support activities as applicable.

+ Lead client workshops, playback sessions, steering updates, design reviews and executive decision discussions with business, operations, engineering, IT and OT stakeholders.

+ Manage engagement financials, including estimates, budget, forecast, staffing, scope change, partner dependencies, and delivery margin.

+ Manage changes in scope and priorities while protecting client outcomes, technical integrity, delivery economics and team sustainability.

+ Identify follow-on opportunities grounded in demonstrated value and client needs and support shaping of the next phase.

+ Build reusable methods, delivery templates, reference patterns, test assets, lessons learned and onboarding materials.

+ Coach junior team members and create a delivery environment with clear ownership, engineering discipline and transparent escalation.

Travel Requirements:

Travel is required for this role and could vary up to 75%

Here's what you need:

+ 5+ years of professional experience, including at least 3 years in consulting, systems integration or client-facing delivery.

+ Practical experience in at least two relevant domains: robotics integration, industrial automation, digital twins, simulation, AI/ML deployment, computer vision, industrial data, edge/cloud or orchestration.

+ Experience managing a project workstream or technical module with responsibility for plan, team, quality, risk, dependencies and stakeholder outcomes.

+ Experience translating operational challenges into measurable outcomes tied to throughput, productivity, quality,…