Integrate analysis outputs with requirements management and ALM tools like Jira and Jama.
Evaluate automated analyses for accuracy and coverage, aiming for an 80% reduction in analysis time.
Benefits
Hybrid Work
Industry leading medical, dental, and vision insurance
Access to a telemedicine service
RRSP program
Personal and sick days
Recreation room with pool table and foosball table
Full Job Description
Job Description
We are seeking a Software Safety Engineer with expertise in Artificial Intelligence (AI), Large Language Models (LLMs), and software safety engineering to support an initiative focused on accelerating Software Failure Mode and Effects Analysis (SW-FMEA).
The successful candidate will contribute to the development of a two-phase dynamic safety architecture: automating the generation of unbiased SW-FMEAs from software architecture specifications and continuously validating safety controls directly within source code through modern CI/CD pipelines.
This is a 2-month contract aimed at modernizing software safety analysis processes, improving coverage, and significantly reducing analysis time as part of the ZHAP improvement initiative.
Responsibilities
Design and develop LLM- and RAG-based solutions to automate SW-FMEA generation from software architectures, SysML specifications, and safety documentation.
Develop automated C/C++ code inspection tools using LLMs and AST parsers to identify failure prevention and detection mechanisms.
Ensure traceability between SW-FMEA analyses and safety mechanisms identified in source code.
Implement automated CI/CD pipeline checks to detect code changes that could compromise critical safety mechanisms.
Integrate analysis outputs with requirements management and ALM tools, including Jira, Jama, and Polarion.
Evaluate the accuracy and coverage of automated analyses, targeting an 80% reduction in analysis time.
