Robotics Technical Architect

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

Accenture's Supply Chain & Engineering group helps industrial clients reinvent how physical operations are designed, simulated, automated, operated and continuously improved. Our Physical AI portfolio brings together digital twins and simulation, robotics intelligence and training, autonomous systems, orchestration, industrial integration, edge and cloud platforms, and managed operations across manufacturing, warehousing, logistics, engineering and other asset-intensive environments.

The Work:

The Robotics Technical Architect is the senior technical authority responsible for defining the architecture, integration, deployment and scaling of robotics intelligence, autonomous systems, fleet orchestration and robotics services within Accenture's Physical AI portfolio. The role requires working knowledge of the broader Physical AI lifecycle, including digital twins, simulation, robot training, industrial data, cloud and edge infrastructure and operational optimization, while bringing deep expertise in robotics systems architecture, robotics software, robot intelligence, multi-robot orchestration and production deployment.

This role is distinct from the end-to-end Physical AI Solutions Architect. It owns the specialist robotics architecture for robotics intelligence platforms, multi-robot orchestration, robot and fleet integration, runtime services and lifecycle operations, working in partnership with solution architects, delivery teams, ecosystem partners and client engineering leaders.

• Define and own end-to-end technical architecture for robotics intelligence platforms, autonomous systems, robotic fleets and robotics services, covering robot hardware, software, middleware, AI models, orchestration, integration and operational support.
• Architect Robotic intelligence platforms spanning perception, localization, SLAM, sensor fusion, motion planning, task planning, autonomous decision logic, robot learning and runtime execution.
• Define architecture patterns for robotics foundation models, synthetic-data pipelines, simulation-based training, model evaluation, simulation-to-real transfer and on-robot inference.
• Architect multi-robot orchestration and fleet-management platforms, including task allocation, traffic management, execution monitoring, exception handling and cross-system coordination.
• Define orchestration services for task allocation, resource scheduling, traffic management, state and event management, exception handling, human intervention, execution monitoring and fleet optimization.
• Design integration patterns across robot OEM systems, fleet managers, ROS/ROS 2, PLC/SCADA, MES, WMS, ERP, IoT platforms, industrial data platforms and site operational workflows.
• Define robotics runtime and platform architecture across cloud, edge and GPU infrastructure, including connectivity, deployment topology, performance, scalability, resilience, security and cost trade-offs.
• Establish robotics observability, telemetry, diagnostics, remote operations, configuration management, software distribution, upgrade, rollback and lifecycle-management patterns.
• Partner with digital-twin and simulation teams to define robotics simulation, virtual commissioning, synthetic-data, robot-training and deployment-validation approaches.
• Define production-readiness and service-management standards covering testing, safety, cybersecurity, commissioning, supportability, operational continuity and transition from pilot to scaled deployment.
• Lead architecture reviews, design…