Senior Manager Digital Architecture (Simulation, Digital Twin, and AI Development)

Caterpillar Inc.•Irving, TX

1d•$172,630 - $258,950•Onsite

About The Position

Your Work Shapes the World at Caterpillar Inc. When you join Caterpillar, you're joining a global team who cares not just about the work we do – but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here – we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it. Help Build the Future of Caterpillar At Caterpillar, technology always has a purpose, which is to solve our customers’ toughest challenges. Through Cat Technology, we are solving problems by building the intelligence layer that connects machines, data, and people to make jobsites safer, more productive, and more sustainable. By combining deep domain expertise in physical systems with software, connectivity, autonomy, and AI, we deliver solutions that work in the real world—on real jobsites, at global scale. You’ll build and deploy against one of the most unique data foundations—over 1.6 million connected assets generating real-world data daily. These data and platform capabilities are enabling the development of AI models, edge computing architectures, and software systems that scale across fleets, products, and industries. The result will be a new generation of machines that continuously learn, improve, and deliver performance at scale. Be Part of What’s Next in Autonomous Construction Sites Construction autonomy is one of the most complex challenges in applied AI, and at Caterpillar, advancements in physical AI, simulation, sensing, and edge computing are turning things that once felt impossible—intelligent machines operating in dynamic jobsites—into reality. Our connected ecosystem brings together massive volumes of high-quality data to create a foundation where engineers like you can build and deploy against. If this work motivates you, we invite you to join our team. In these roles, you’ll work at the intersection of the physical and digital worlds. You’ll help design and deliver intelligent systems that enable machines to perceive their environment, make informed decisions, and support safer, more productive operations. Job Summary: The Senior Manager, Digital Architecture – Simulation, Digital Twin & AI Development leads the architecture organization responsible for enabling machines to learn, improve, and scale through simulation, digital twins, synthetic data, AI model development, and AI Factory capabilities. This leader defines the strategy, architecture, and technical roadmap for the platforms, infrastructure, and software ecosystems that support the complete lifecycle of Physical AI development—from data generation and simulation to model training, fine-tuning, and validation. The role is accountable for the architecture of digital twin platforms, simulation environments, synthetic data pipelines, AI development platforms, and AI Factory infrastructure, including GPU compute, high-performance storage, networking, orchestration, MLOps, and model lifecycle management capabilities. Partnering with engineering, data science, perception, and robotics teams, this leader ensures that real-world machine data, virtual environments, and AI development workflows operate as a connected ecosystem that accelerates innovation and continuously improves autonomous system performance. Need to be able to architect an integrated ecosystem where digital twins generate insights, simulation creates learning opportunities, AI Factories train and fine-tune models, and autonomous machines continuously improve through operational feedback loops. This individual understands not only the technology stack, but also how to transform it into a strategic capability that accelerates Physical AI adoption and creates a sustainable competitive advantage. Success in this role is measured by the organization’s ability to rapidly develop, validate, and scale Physical AI capabilities while maximizing the value of simulation, digital twins, AI infrastructure, and the NVIDIA ecosystem to create increasingly intelligent, autonomous, and adaptable machines.

Requirements

Expert Knowledge of techniques and tools that promote effective analysis; ability to determine the root cause of organizational problems and create alternative solutions that resolve these problems.
Expert knowledge of processes, techniques and factors that affect data architecture; ability to design blueprints on how to integrate data resources for business processes and functional support. Ability to utilize design methodologies, tools and techniques to convert business requirements and logical models into a technical design.
Expert understanding of effective communication concepts, tools and techniques; ability to effectively transmit, receive, and accurately interpret ideas, information, and needs through the application of appropriate communication behaviors.
Expert knowledge of leadership concepts and ability to use strategies and skills to enlist others in setting, embracing and achieving objectives.
Expert knowledge of technologies and methods to design processing mechanisms and roadmaps to execute business application systems; ability to design these roadmaps and deploy supportive interfaces for end-users to access related systems, in accordance with standards and processes.
Deep experience defining and scaling digital twin ecosystems that model machines, autonomous systems, worksites, and operational environments. Candidates should understand how digital twins connect real-world machine data, simulation platforms, and AI development workflows to accelerate innovation and improve operational performance.
Strong expertise in simulation architectures, synthetic data generation, scenario modeling, and virtual validation environments used to train, test, and improve autonomous systems. Candidates should understand how simulation reduces development risk and enables machines to learn and improve before deployment into real-world environments.
Proven experience architecting enterprise-scale AI Factory environments, including GPU compute clusters, high-performance storage, networking, orchestration platforms, workload scheduling, distributed training, model development environments, and AI platform operations. Candidates should understand both the infrastructure and software components required to scale AI development.
Hands-on experience with the NVIDIA Physical AI stack, including NVIDIA Omniverse, NVIDIA Cosmos, NVIDIA Isaac, DGX systems, CUDA, NeMo, TensorRT, NIMs, and AI Factory technologies. Candidates should understand how these technologies work together to support simulation, digital twins, synthetic data generation, model development, and autonomous systems at scale.
Demonstrated ability to define long-term technology strategy, build and lead high-performing architecture organizations, influence executive stakeholders, and translate emerging AI technologies into scalable enterprise capabilities. Candidates should have a track record of delivering complex AI, simulation, and digital twin initiatives that create measurable business and operational value.
Progressive career in software engineering and architecture with a focus on data (typically 12years+)
Demonstratable experience leading technology development for enterprise scale systems in public cloud and hybrid eco-systems
Team leadership, management and budget responsibility experience (typically 5+ years)

Responsibilities

Leads the architecture organization responsible for enabling machines to learn, improve, and scale through simulation, digital twins, synthetic data, AI model development, and AI Factory capabilities.
Defines the strategy, architecture, and technical roadmap for the platforms, infrastructure, and software ecosystems that support the complete lifecycle of Physical AI development—from data generation and simulation to model training, fine-tuning, and validation.
Accountable for the architecture of digital twin platforms, simulation environments, synthetic data pipelines, AI development platforms, and AI Factory infrastructure, including GPU compute, high-performance storage, networking, orchestration, MLOps, and model lifecycle management capabilities.
Partners with engineering, data science, perception, and robotics teams to ensure that real-world machine data, virtual environments, and AI development workflows operate as a connected ecosystem that accelerates innovation and continuously improves autonomous system performance.
Architects an integrated ecosystem where digital twins generate insights, simulation creates learning opportunities, AI Factories train and fine-tune models, and autonomous machines continuously improve through operational feedback loops.
Transforms the technology stack into a strategic capability that accelerates Physical AI adoption and creates a sustainable competitive advantage.
Ensures the organization's ability to rapidly develop, validate, and scale Physical AI capabilities while maximizing the value of simulation, digital twins, AI infrastructure, and the NVIDIA ecosystem to create increasingly intelligent, autonomous, and adaptable machines.