C

Caterpillar

Makes heavy machinery, engines and gas turbines

AI Architect

Robotics & Autonomous SystemsConfirmed live in the last 24 hours
Full-timeShanghai, ChinaNo salary listedIn-person

About the Job

Requirements

  • A Master's degree in Artificial Intelligence, Computer Science, Robotics, Autonomous Systems, Electrical Engineering, Data Science, Systems Engineering, Mining Engineering, or a related technical discipline is required.
  • At least 10 years of experience in software engineering, systems engineering, autonomy, robotics, or platform architecture is required.
  • At least 5 years of experience designing and deploying AI solutions in production environments is required.
  • Experience delivering large-scale enterprise or industrial AI platforms is required.
  • Demonstrated leadership in cross-functional technology initiatives is required.
  • Technical competencies include generative AI; large language models including GPT, Claude, Gemini, and Llama; agentic AI; multi-agent systems; machine learning; deep learning; reinforcement learning; prompt engineering; and retrieval-augmented generation architectures.
  • Technical competencies in physical and autonomous intelligence include physical AI, embodied AI, world models, autonomous decision-making, behavioral AI systems, human-AI collaboration, robotics foundation models, and edge AI.
  • Autonomous vehicle competencies include autonomous truck systems, perception systems, localization and mapping, sensor fusion, path planning, controls architecture, vehicle intelligence, and functional safety.
  • Digital platform and cloud competencies include Azure AI Services, Azure OpenAI, AWS, Kubernetes, microservices architecture, distributed computing platforms, event-driven systems, and REST APIs.
  • Data and knowledge competencies include knowledge graphs, ontology engineering, vector databases, semantic search, digital twin architecture, data governance, and enterprise knowledge systems.
  • Programming competencies include Python, C++, C#, and Java.
  • Leadership competencies include strategic thinking, systems thinking, innovation leadership, technical excellence, cross-functional collaboration, executive communication, customer focus, problem solving, influencing without authority, and business acumen.

Responsibilities

  • Define enterprise AI architecture strategy and technical roadmaps.
  • Develop architecture standards, reference designs, and reusable frameworks.
  • Translate mining business challenges into scalable AI-enabled solutions.
  • Lead solution design reviews and technical governance activities.
  • Evaluate emerging AI technologies and identify strategic adoption opportunities.
  • Lead architecture for intelligent mining equipment and fleet operations, including autonomous haulage systems, AI-powered haul trucks, fleet management systems, route optimization, mission planning, traffic management, productivity optimization, site orchestration, and mine operations intelligence.
  • Define AI-enabled vehicle intelligence architecture and support development of AI-assisted autonomous decision-making capabilities.
  • Architect systems for context-aware operations, mission understanding, adaptive decision-making, fleet collaboration, operational optimization, and human-AI interaction.
  • Work with autonomy, controls, perception, and vehicle platform teams.
  • Define architecture strategies for physical AI systems operating in large-scale mines and enable intelligent interaction among autonomous trucks, mine infrastructure, digital platforms, human operators, and AI agents.
  • Develop architectures for real-time perception, world understanding, reasoning, planning, and action execution; establish frameworks for closed-loop learning and operational adaptation.
  • Design embodied AI intelligence systems that enable autonomous equipment to understand complex mine environments, learn from operational data, adapt to changing conditions, and coordinate with other autonomous assets.
  • Architect AI assistant capabilities across mining operations and define AI workflows that transform operational data into actionable insights.
  • Enable AI-driven decision support and workflow automation.
  • Establish architecture for Atlas Platform, MineStar Ecosystem, connected equipment platforms, operational data platforms, and cloud infrastructure.
  • Define interoperability standards across global systems and build scalable AI infrastructure for enterprise deployment.
  • Ensure platform reliability, security, and maintainability.
  • Architect solutions supporting digital twins, knowledge graphs, semantic search, operational intelligence, and enterprise knowledge management.
  • Define ontology and domain-modeling approaches, enable capture and reuse of operational expertise and tribal knowledge, and create intelligence layers for contextual AI reasoning.
  • Define enterprise AI data strategy and establish standards for data quality, data governance, metadata management, and AI data pipelines.
  • Design architectures supporting real-time analytics, edge-to-cloud integration, and AI model lifecycle management; ensure scalability and future extensibility.
  • Lead responsible AI adoption and governance, define AI lifecycle management processes, and establish monitoring and validation frameworks.
  • Ensure compliance with data privacy requirements, cybersecurity standards, industry regulations, and corporate governance policies; develop AI risk management strategies.
  • Serve as technical leader across AI, autonomy, and digital platform initiatives; mentor engineers, architects, and technical leads.
  • Lead architecture reviews and strategic technology evaluations, support executive decision-making and customer engagements, and influence long-term product and platform strategy.

Desired Qualifications

  • A Ph.D. in Artificial Intelligence, Robotics, Machine Learning, Autonomous Systems, Computer Science, Electrical Engineering, Mining Engineering, or a related technical field is preferred.
  • Experience in autonomous mining, autonomous trucks, heavy equipment, mining technology, construction technology, industrial automation, robotics, or intelligent transportation systems.
  • Experience with MineStar or equivalent fleet management platforms.
  • Experience developing AI-enabled equipment solutions.
  • Experience architecting AI assistants in industrial environments.
  • Experience deploying AI to edge devices or autonomous platforms.
  • Expertise in digital twin architecture and operational simulation.
  • Experience with agentic AI frameworks.
  • Publications in AI, robotics, autonomous systems, physical AI, or mining technologies; patents related to AI, autonomy, robotics, or intelligent industrial systems; or contributions to leading-edge AI research or technology commercialization.

About the Company

Caterpillar

Makes heavy machinery, engines and gas turbines

Caterpillar makes construction and mining machines, diesel and natural gas engines, industrial gas turbines and locomotives for contractors, mines, energy companies and data center builders. It is the world's largest maker of construction and mining equipment, and its yellow Cat bulldozers and excavators work in nearly every country. Customers buy or rent machines through independent Cat dealers, while its engines and turbines generate electricity and push natural gas through pipelines. Caterpillar earns money from equipment sales and from the parts and repairs that dealers supply over a machine's working life. It was formed in 1925 when California's Holt and Best tractor companies merged, and it is based in Irving, Texas.

Company size
10,001+
Company stage
IPO
Headquarters
Irving, TX
Founded
1925

Recently Posted Jobs

Explore more opportunities at Caterpillar

See more jobs