Job Summary

The Senior Product Safety Architect, is responsible for defining and owning the end-to-end safety architecture for our L4 autonomous driving system, translating safety goals and hazard analyses into concrete system-level design decisions. This role requires a strong foundation in functional safety (UL 4600, ISO 26262) combined with working knowledge of AI/ML safety challenges specific to autonomous systems. The incumbent will partner closely with perception, prediction, planning, and control teams to embed safety requirements throughout the development lifecycle, and will bring an architecture mindset to ensure that safety properties are verifiable, traceable, and defensible in our safety case.

Essential Responsibilities

• Define and own the safety architecture for our Driver Out autonomous system, establishing the system decomposition, safety mechanisms, and architectural constraints that instantiate our UL 4600 safety case claims.
• Derive functional safety concepts and technical safety concepts from HARA outputs, and allocate safety requirements to AV system components (perception, prediction, planning, actuation, fallback) with clear architectural rationale per UL 4600 and ISO 26262.
• Own and manage the safety plan according UL4600 and ISO26262 including a schedule to hit the company’s product launches.
• Identify and address AI/ML-specific safety risks including distributional shift, model uncertainty, and failure mode opacity; define architectural mitigations (e.g., runtime monitors, confidence thresholds, safe fallback behaviors) to maintain safety goals in the presence of learned components.
• Collaborate with the development teams on every aspect of the safety plan through appropriate processes and methods to ensure on-time delivery of mature work products.
• Create, maintain and review safety work products such as HARA, FSC, TSC, FTA, FMEA, SPFM/LFM, PMHF, and DFA; extend these analyses to cover ML component failure modes and ODD boundary conditions specific to L4 autonomous operation.
• Communicate with all required stakeholders to identify and define technical/ system requirements and safety requirements tied to the safety goals.
• Ability to effectively communicate and explain functional safety concepts to non-safety engineers.
• Ensure that functional safety confirmation measures such as audits and assessments are planned and completed.
• Excellent communication and presentation skills.
• Hands-on with an analytical mindset and a proven track record of problem-solving.
• An enthusiasm for cutting-edge innovation in self-driving technologies and safety products

Skills and Abilities

Success in this role typically requires the following competencies:

• Strong working knowledge and ability to apply the following safety frameworks:
• HARA
• FMEA
• FTA
• FMEDA
• DFA
• SOTIF (ISO 21448) / AI safety risk assessment
• UL 4600 CAE (Claim-Argument-Evidence) safety case construction
• Requirements capture and traceability; safety metrics definition; system architecture decomposition and interface definition across AV subsystems
• Excellent communication and presentation skills.
• Hands-on with an analytical mindset and a proven track record of problem-solving.
• An enthusiasm for cutting-edge innovation in self-driving technologies and safety products
• Ability to clarify and document fuzzy requirements and challenges such that a project team can efficiently and effectively solve problems.
• An ability to clearly and concisely communicate technical concepts including root cause analysis, technical challenges and their solutions, and results backed by data.
• An ability to communicate effectively with both technical and non-technical people and teams.
• Understanding of software and hardware development life cycles, integration processes, and test/validation complexity

Qualifications and Experience

Candidates most successful in this role typically hold the following qualifications or comparable knowledge or experience:

Required

• Bachelor’s degree or equivalent experience in Systems Engineering, Electrical Engineering, Computer Science, or a related technical discipline
• 7+ years of related work experience, with at least 3 years in autonomous vehicle or advanced robotics system architecture, and demonstrable exposure to AI/ML safety challenges in safety-critical applications