Senior Autonomy Engineer

Caterpillar Inc.•Mossville, IL

3d•$112,710 - $183,140•Onsite

About The Position

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. The Senior SOTIF Engineer will be a key member of the AI Product Assurance team, responsible for leading and executing activities related to Safety of the Intended Functionality (SOTIF) for complex, AI-enabled and autonomous systems. This role focuses on ensuring that risks arising from functional insufficiencies, performance limitations, and reasonably foreseeable misuse are systematically identified, mitigated, and monitored across the product lifecycle. As a senior technical contributor, you will work across engineering, product, and safety teams to define SOTIF strategies, develop safety arguments, and generate credible evidence supporting product release and safe operation. The role requires deep technical expertise in complex systems, autonomy, AI/ML, and international safety standards, combined with the ability to translate theory into scalable, industrial practice.

Requirements

Bachelor’s or Master’s degree in Robotics, Electrical Engineering, Mechanical Engineering, Computer Engineering, Computer Science, or a related field from an accredited institution.
Problem Solving: Working knowledge in automotive, machine, or industrial embedded network communication software development fields. Capable of developing and executing a data acquisition plan for detect radar and camera sensors. Ability to execute projects and optimize development strategies based on a large repository of data
Familiarization with core robotics principles
Software Development Life Cycle: Strong understanding of software engineering principles
Familiarity with Agile methodologies and iterative development practices
Ability to write clean, maintainable, and scalable code across the full stack
Skilled in debugging, testing, and deploying software in production environments
Programming: Skilled at programming in C++
Proficient in object-oriented design and software architecture
Knowledgeable in real-time systems and embedded programming
Comfortable working with version control tools like Git

Nice To Haves

Deep expertise in Safety of the Intended Functionality (SOTIF) and it's application to Autonomous and AI-enabled systems.
Understanding of regulatory compliance standards for safety including but not limited to ISO21448, ISO26262, ISO19014, PAS8800.
Experience with AI/ML systems, including dataset limitations, generalization issues, out-of-distribution behavior, and monitoring strategies supporting verification and validation strategies for complex systems, including simulation, statistical testing, shadow mode, and field data analysis.
Master's or PhD in related field preferred.
Proven experience with safety analysis methods and evidence-based assurance in an engineering environment preferred.

Responsibilities

Lead the definition and execution of SOTIF activities for AI-enabled, autonomous, and safety-related control systems across development and operation phases.
Develop and maintain the SOTIF lifecycle aligned with ISO 6135 (EMM equivalent of ISO 21448) and integrated with functional safety, systems engineering, and AI safety activities.
Identify hazards, functional insufficiencies, triggering conditions, and reasonably foreseeable misuse at vehicle, system, and element levels.
Define Operational Design Domains (ODDs), behaviors, scenarios, and boundary conditions, including insufficiencies, limitations, and degradations.
Drive scenario-based safety analysis, including known and unknown scenario discovery, coverage assessment, and risk-based prioritization.
Specify and evaluate SOTIF mitigation measures, including functional modifications, restrictions, monitoring strategies, and handover mechanisms.
Define verification and validation strategies combining simulation, structured testing, data-driven analysis, and in-field monitoring.
Develop quantitative and qualitative safety metrics, including scenario coverage, criticality, discovery rates, and residual risk arguments.
Contribute to the creation of safety cases, assurance arguments, and technical construction files supporting product release decisions.
Support in-service monitoring, incident analysis, and continuous assurance through data collection, observers, and runtime safety mechanisms.
Collaborate with AI, autonomy, and platform teams to ensure tool credibility, data quality, and traceability of evidence across the lifecycle.
Participate in internal and external standardization efforts and ensure alignment with evolving safety and AI standards.