Functional Safety AI Principal Engineer

We are seeking a Functional Safety AI Principal Engineer to connect AI functional safety to software and quality engineering at Ford. As a Principal technical authority, you will bridge architecture, safety, software quality, AI/ML engineering, and program execution.

Responsibilities:

• Implement guardrails for safety within existing quality requirements enforced through the same development pipeline, quality gates, and metrics.
• Drive system safety architecture and assurance strategy for AI across Ford's ADAS/AD, driver-monitoring, and connected/embodied-AI programs.
• Lead adoption of emerging AI-safety standards and process frameworks and prepare Ford for AI-specific regulation.
• Assess AI maturity within projects, process frameworks, and Ford infrastructure to develop an AI in FuSa Health Dashboard.
• Work with Ford Connected Vehicle Software and Product Data Integrity, and supplier engineering teams to identify safety-related process and work product gaps and recommend best practice solutions.
• Develop a capability maturity plan working with engineering stakeholders.
• Report to the Director of the Office of Functional Safety Assurance (OFSA).

Requirements:

• FuSa/AI Technical Leadership: Apply, demonstrate, and champion best-in-class methods, tools, and practices to ensure embedded software achieves safety.
• AI in FuSa Software Health Dashboard Ownership: Lead the development of the Health Dashboard for the enterprise, including its metrics and criteria for maturity.
• Strategic leadership: Provide strategic direction and leadership to the safety community, fostering a culture of collaboration, innovation, and excellence.
• Ownership of the AI in FuSa strategy: Responsible for the definition and deployment of maturity model, framework for safe AI development, and AI-enhanced confirmation.
• Cross-functional collaboration: Collaborate closely with cross-functional teams to drive execution to program timelines.
• FuSa Software-related escapes: Apply system engineering, risk analysis, troubleshooting, and root cause analysis methods to find software-related issues and close the loop to process, methods, and tools gaps.
• Alignment of FuSa, Cyber, and Quality Assurance: Align and exploit synergies with SQA where this helps drive FuSa maturity.
• Continuous improvement: Drive continuous improvement initiatives to optimize software development and deployment processes, tools, and methodologies, enhancing effectiveness.
• Communication: Provide consistent health status, insights, risks, and opportunities to executive leadership and stakeholders.