Robotics Technical Architect

Accenture•St. Louis, MO

11d•Hybrid

About The Position

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, cloud and edge platforms, and managed operations across manufacturing, warehousing, logistics, engineering and other asset-intensive environments. 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.

Requirements

8+ years of professional experience in robotics engineering, robotics software, autonomous systems, industrial automation or related fields.
Demonstrated experience architecting and deploying industrial or commercial robotics systems in production environments.
Strong proficiency in ROS/ROS 2, Python and C++ for robotics applications and platform integration.
Hands-on experience with robotics intelligence capabilities such as perception, localization, SLAM, motion planning, task planning, sensor fusion, controls or autonomous navigation.
Experience with fleet management, multi-robot coordination, orchestration platforms or distributed robotic systems.
Experience integrating robotics with industrial systems and protocols such as PLC/SCADA, OPC UA, MQTT, EtherNet/IP, MES, WMS or ERP.
Understanding of cloud, edge and GPU-enabled deployment patterns, containers, APIs, event-driven integration, observability and production 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

Experience with NVIDIA Isaac Sim, Isaac ROS, Omniverse, Jetson, IGX, CUDA-enabled robotics or comparable robotics and simulation ecosystems.
Experience defining architecture decisions, integration contracts, non-functional requirements, risks, test strategy and production-readiness controls.
Strong client-facing communication skills with the ability to translate robotics architecture and operational implications for business, engineering, IT and OT stakeholders.
Experience with robotics foundation models, robot learning, reinforcement or imitation learning, synthetic data and simulation-to-real workflows.
Experience architecting Unified Operations Platforms, robotics control towers, multi-vendor fleet orchestration or managed fleet operations.
Experience with industrial robots, cobots, AMRs/AGVs, mobile manipulation, machine vision and autonomous inspection systems across multiple vendors
Experience with Kubernetes, Docker, CI/CD, MLOps/DevOps, edge orchestration, telemetry, remote support and robotics software lifecycle management.
Knowledge of functional-safety standards such as ISO 10218 and ISO/TS 15066, safeguarding, risk assessment, responsible AI and OT cybersecurity.
Experience taking robotics programs from proof of value through production deployment, multi-site rollout and lifecycle operations.
Experience in manufacturing, warehousing, logistics, engineering, laboratories, data centers or other asset-intensive operations.
Experience in consulting, systems integration, product engineering or client-facing delivery, including solutioning and pursuit support.

Responsibilities

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 authority, architecture decision records, technical risk management and engineering governance throughout pursuits and delivery.
Provide technical leadership and mentorship to robotics, automation, AI and platform engineering teams and establish reusable engineering standards and practices.
Support pre-sales and solutioning through technical discovery, scoping, architecture proposals, estimates, demonstrations, partner selection, risk assessment and delivery transition.
Build reusable reference architectures, adapters, integration patterns, test assets and accelerators for robotics intelligence, UOP, fleet operations and managed robotics services.
Collaborate with ecosystem partners including NVIDIA, robotics OEMs, industrial automation providers, fleet-management vendors, cloud providers and industrial software companies.