Job Overview
The Forti
OS Release QA team is a group of over 90 staff dedicated to ensuring Fortinet products meet elite market standards before release. We are seeking an AI Application Developer to architect an end-to-end, closed-loop release cycle. You will design an AI-governed control plane that autonomously manages the software lifecycle: reasoning over feature specifications to create test plans, executing and verifying tests, managing the bug lifecycle, and ultimately generating customer-facing documentation and videos once a feature is verified.
Your goal is to minimize manual toil while ensuring elite quality and providing immediate value to the end-user upon release.
Future Duties and Responsibilities
Design systems using LLMs to ingest feature specifications and technical documentation to autonomously generate comprehensive test plans and high-coverage test scripts
Utilize AI to author test cases derived from design requirements rather than existing code, ensuring that tests verify the intended functionality and avoid implementation-based confirmation bias.
Develop and deploy AIOps solutions to process massive log records and metrics from automation jobs, identifying the "few that matter" to automate root cause analysis and reduce manual triage toil.
Implement machine learning models for test case prioritization to maximize fault detection and optimize execution throughput within the CI/CD pipeline.
Build agents for automatic bug filing, tracking, and verification, including performing autonomous re-testing to verify fixes before they reach human review.
Develop AI systems to autonomously generate technical documentation and instructional video content for customers following successful feature verification. Use LLMs to synthesize technical specs and verification results into structured, human-readable explanations and multimedia artifacts to accelerate customer onboarding.
Embed risk-weighted decision models to ensure that final release acknowledgements are backed by auditable AI-driven insights while preserving human oversight for high-impact decisions
Required Qualifications to be Successful in this Role
Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related technical field.
Experience:
2–3 years of experience building machine learning, natural language processing (NLP), or generative AI-driven applications.
Strong proficiency in Python and familiarity with common machine learning libraries such as Num Py, Pandas, Scikit-learn, Tensor Flow, or PyTorch.
Proven experience building applications with Large Language Models (LLMs) using strategies like prompt engineering and Retrieval-Augmented Generation (RAG).
Hands-on experience with CI/CD tools, containerization (Docker, Kubernetes), and the integration of AI into automated testing toolchains.
Ability to reason over complex "brownfield" tasks where AI must interact with large, existing codebases and distributed systems.
Effective communication skills to explain AI-driven insights, behaviors, and constraints to both technical QA staff and non-technical stakeholders.
Preferred Skills & Knowledge
The Canada base salary range for this full-time position is expected to be between $107,000 - $179,000 annually. Wage ranges are based on various factors including the labour market, job type, and job level. Exact salary offers will be determined by factors such as the candidate’s subject knowledge, skill level, qualifications, and experience.
Fortinet strives to provide…
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