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AI Architect

cat855 open roles

Where
Shanghai, Shanghai
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Early applications get read.

13.3% of postings close within 7 days. Measured by our own scanner across the market. cat postings stay open a median of 12 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.6%3 days
  3. 13.3%7 days
  4. 21.3%14 days
  5. 35.7%30 days
  6. 59.1%60 days
This job: posted today

cat median: 12 days open

The posting

Career Area:

Technology, Digital and Data

Job Description:

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.

Position Summary

We are seeking a visionary and technically accomplished AI Solution Architect to lead the architecture, design, and deployment of next-generation AI-powered solutions for autonomous mining operations and digital platform ecosystems.

This role will define the technology roadmap and architecture strategy for the convergence of Artificial Intelligence, Physical AI, Autonomous Equipment, Digital Twins, Enterprise Knowledge Platforms, and Agentic AI Systems. The successful candidate will bridge mining operations, autonomy engineering, software platforms, data architecture, and AI innovation to create intelligent, scalable, and commercially deployable solutions.

The ideal candidate possesses deep expertise in AI technologies, autonomous vehicle systems, industrial digital platforms, and large-scale enterprise architectures, with a passion for transforming the future of mining through intelligent systems.

Position Vision

Drive the convergence of Physical AI, Autonomous Equipment, Digital Platforms, Digital Twins, and Agentic AI to create the intelligent mine of the future.

This role will serve as a key technical leader in shaping AI-enabled mining operations by integrating:

  • Autonomous Haulage Systems (AHS)
  • AI-Powered Mining Trucks
  • Fleet Intelligence
  • Site Orchestration
  • Digital Twins
  • Knowledge Graphs
  • Enterprise AI Assistants
  • Multi-Agent Systems
  • Mining Operational Intelligence

Key Responsibilities

1. AI Strategy & Solution Architecture

  • Define enterprise AI architecture strategy and technical roadmap.
  • 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.

2. Autonomous Mining & AI Truck Intelligence

Lead architecture for next-generation intelligent mining equipment and fleet operations.

Design AI solutions supporting:

  • Autonomous Haulage Systems (AHS)
  • AI-Powered Haul Trucks
  • Fleet Management Systems
  • Route Optimization
  • Mission Planning
  • Traffic Management
  • Productivity Optimization
  • Site Orchestration
  • Mine Operations Intelligence

Key Responsibilities

  • Define AI-enabled vehicle intelligence architecture.
  • Support development of AI-assisted autonomous decision-making capabilities.
  • Architect systems enabling:Context-aware operations Mission understanding Adaptive decision making Fleet collaboration Operational optimization Human-AI interaction
  • Work closely with autonomy, controls, perception, and vehicle platform teams.

3. Physical AI & Autonomous Systems

Lead the development of Physical AI architectures for autonomous mining environments.

Key Responsibilities

  • Define architecture strategies for Physical AI systems operating in large-scale mines.
  • Enable intelligent interaction between:Autonomous trucks Mine infrastructure Digital platforms Human operators AI agents
  • Develop architectures supporting:Real-time perception World understanding Reasoning Planning Action execution
  • Establish frameworks for closed-loop learning and operational adaptation.

Embodied AI

  • Design intelligence systems based on embodied AI principles.
  • Enable autonomous equipment to:Understand complex mine environments Learn from operational data Adapt to changing conditions Coordinate with other autonomous assets

4. Generative AI & Agentic Systems

Define next-generation AI Assistant and Agent-based architectures.

Design solutions supporting:

  • Mine Supervisors
  • Dispatch Operators
  • Fleet Managers
  • Maintenance Teams
  • Site Managers
  • Production Planning Teams

Technology Areas

  • Large Language Models (LLMs)
  • Agentic AI
  • Multi-Agent Systems
  • AI Copilots
  • Retrieval Augmented Generation (RAG)
  • Enterprise Search
  • Autonomous Decision Support

Responsibilities

  • Architect AI Assistant capabilities across mining operations.
  • Define AI workflows that transform operational data into actionable insights.
  • Enable AI-driven decision support and workflow automation.

5. Digital Platform Architecture

Define AI integration strategies across enterprise mining platforms.

Responsibilities

  • Establish architecture for:Atlas Platform MineStar Ecosystem Connected Equipment Platforms Operational Data Platforms Cloud Infrastructure
  • Define interoperability standards across global systems.
  • Build scalable AI infrastructure supporting enterprise deployment.
  • Ensure platform reliability, security, and maintainability.

6. Digital Twin & Knowledge Intelligence

Lead design of enterprise knowledge and operational intelligence systems.

Responsibilities

  • Architect solutions supporting:Digital Twins Knowledge Graphs Semantic Search Operational Intelligence Enterprise Knowledge Management
  • Define ontology and domain modeling approaches.
  • Enable capture and reuse of operational expertise and tribal knowledge.
  • Create intelligence layers supporting contextual AI reasoning.

7. Data Architecture & Governance

Responsibilities

  • Define enterprise AI data strategy.
  • Establish standards for:Data Quality Data Governance Metadata Management AI Data Pipelines
  • Design architectures supporting:Real-time analytics Edge-to-cloud integration AI model lifecycle management
  • Ensure scalability and future extensibility.

8. AI Governance & Responsible AI

Responsibilities

  • Lead Responsible AI adoption and governance.
  • Define AI lifecycle management processes.
  • Establish monitoring and validation frameworks.
  • Ensure compliance with:Data Privacy Requirements Cybersecurity Standards Industry Regulations Corporate Governance Policies
  • Develop AI risk management strategies.

9. Technical Leadership

Responsibilities

  • 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.
  • Influence long-term product and platform strategy.

Required Qualifications

Education

Minimum Requirements

Master's Degree in:

  • Artificial Intelligence
  • Computer Science
  • Robotics
  • Autonomous Systems
  • Electrical Engineering
  • Data Science
  • Systems Engineering
  • Mining Engineering
  • Related Technical Discipline

Preferred

Ph.D. in:

  • Artificial Intelligence
  • Robotics
  • Machine Learning
  • Autonomous Systems
  • Computer Science
  • Electrical Engineering
  • Mining Engineering
  • Related Technical Field

Professional Experience

Required

  • 10+ years of experience in software engineering, systems engineering, autonomy, robotics, or platform architecture.
  • 5+ years of experience designing and deploying AI solutions in production environments.
  • Proven experience delivering large-scale enterprise or industrial AI platforms.
  • Demonstrated leadership in cross-functional technology initiatives.

Preferred Industry Experience

  • Autonomous Mining
  • Autonomous Trucks
  • Heavy Equipment
  • Mining Technology
  • Construction Technology
  • Industrial Automation
  • Robotics
  • Intelligent Transportation Systems

Technical Competencies

Artificial Intelligence

  • Generative AI
  • Large Language Models (GPT, Claude, Gemini, Llama)
  • Agentic AI
  • Multi-Agent Systems
  • Machine Learning
  • Deep Learning
  • Reinforcement Learning
  • Prompt Engineering
  • RAG Architectures

Physical AI & Autonomous Intelligence

  • Physical AI
  • Embodied AI
  • World Models
  • Autonomous Decision Making
  • Behavioral AI Systems
  • Human-AI Collaboration
  • Robotics Foundation Models
  • Edge AI

Autonomous Vehicle Technologies

  • Autonomous Truck Systems
  • Perception Systems
  • Localization & Mapping
  • Sensor Fusion
  • Path Planning
  • Controls Architecture
  • Vehicle Intelligence
  • Functional Safety

Digital Platforms & Cloud Technologies

  • Azure AI Services
  • Azure OpenAI
  • AWS
  • Kubernetes
  • Microservices Architecture
  • Distributed Computing Platforms
  • Event-Driven Systems
  • REST APIs

Data & Knowledge Systems

  • Knowledge Graphs
  • Ontology Engineering
  • Vector Databases
  • Semantic Search
  • Digital Twin Architecture
  • Data Governance
  • Enterprise Knowledge Systems

Programming

  • Python
  • C++
  • C#
  • Java

Preferred Qualifications

  • 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.

Research & Innovation

Preferred candidates may possess:

  • Publications in AI, Robotics, Autonomous Systems, Physical AI, or Mining Technologies.
  • Patents related to AI, autonomy, robotics, or intelligent industrial systems.
  • Contributions to leading-edge AI research or technology commercialization.

Leadership Competencies

  • Strategic Thinking
  • Systems Thinking
  • Innovation Leadership
  • Technical Excellence
  • Cross-Functional Collaboration
  • Executive Communication
  • Customer Focus
  • Problem Solving
  • Influencing Without Authority
  • Business Acumen

Success Metrics

The successful candidate will:

✅ Define the AI architecture roadmap for autonomous mining and digital platforms

✅ Deliver next-generation AI Truck and Fleet Intelligence capabilities

✅ Enable enterprise-scale AI Assistants and Agentic AI solutions

✅ Establish foundational Digital Twin and Knowledge Intelligence architectures

✅ Accelerate customer adoption of AI-enabled mining technologies

✅ Drive integration of Physical AI, Autonomous Equipment, and Digital Platforms into commercially deployable solutions

✅ Help build the intelligent mine of the future

Posting Dates:

November 4, 2026 - December 3, 2026

Caterpillar is an Equal Opportunity Employer. Qualified applicants of any age are encouraged to apply

Not ready to apply? Join our Talent Community.

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