Physical AI Delivery Manager

Accenture•Atlanta, GA

2d•Remote

About The Position

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.

Requirements

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, safety, capital or operating cost, commissioning risk, uptime or workforce effectiveness.
Ability to review technical designs, challenge assumptions, facilitate decisions and communicate implications to non-technical stakeholders.
Understanding of production-readiness practices, testing, change control, cybersecurity, safety and operational support in industrial environments.
Experience working with manufacturing, warehousing, logistics, engineering, data-center, laboratory or other asset-intensive operations.
Bachelor's degree or equivalent (minimum 12 years) work experience. (If associate degree, must have a minimum of 6 years’ work experience)

Nice To Haves

Hands-on experience with ROS 2, simulation tools, digital-twin platforms, industrial automation, AI/ML deployment, cloud/edge platforms or OT integration.
Experience with NVIDIA, Siemens, Dassault Systemes, PTC, Ansys, Rockwell, SAP, hyperscaler, robotics or automation ecosystems.
Experience supporting pursuit solutioning, estimates, proposals, client orals and commercial shaping.
Experience taking a proof of concept through pilot, production deployment and multi-site scale.
Industry process knowledge in manufacturing, warehousing, logistics, engineering, capital projects, data centers or life-sciences operations.
Project management, Agile, SAFe, Lean, Six Sigma, cloud, architecture, cybersecurity or relevant industrial technology certification.

Responsibilities

Lead delivery workstreams 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.