Our financial services client is seeking an AI Security Automation Engineer to develop and operationalize AI-assisted cybersecurity workflows using agentic AI, LLMs, and security operations processes - JP Join a cybersecurity team advancing AI initiatives within Incident Response and security operations.

This role focuses on designing, testing, and operationalizing AI-assisted and agentic workflows supporting investigation efficiency, automation, and security analysis activities.

The position combines hands-on AI workflow development with cybersecurity investigation and operational security expertise across enterprise-scale environments.

The contractor will work independently while collaborating closely with Incident Response stakeholders and technology partners.

Contract, 6 months (Extension possible) Toronto, Hybrid (2 days on site/remote) Must Haves 7+ years in Incident Response , threat detection , digital forensics , security operations , or threat intelligence Hands-on work with agentic AI workflows , LLM-based applications , automation pipelines , and AI-assisted workflows Practical familiarity with tool calling , retrieval-augmented generation , workflow orchestration , prompt engineering , and human-in-the-loop review Experience with Lang

Graph , Lang

Chain , Semantic Kernel , Auto

Gen , CrewAI , OpenAI Assistants/Agents SDKs ,



Git

Hub Copilot SDK , or Azure AI Foundry Postsecondary education Nice to Have Qualified security certification such as CISSP, GCIH, GCFA, GCFE, or GCFR Experience with SIEM, SOAR, EDR, case management, or threat intelligence platforms Responsibilities Design and evaluate agentic AI workflows supporting Incident Response use cases including alert triage, investigation planning, evidence summarization, and reviewer routing Build AI-enabled workflow prototypes using agent development frameworks and SDKs Develop structured agent workflows involving retrieval-augmented generation, tool calling, workflow routing, and human approval checkpoints Create evaluation approaches for AI-assisted security workflows including backtesting, hallucination analysis, regression testing, and precision or recall measurement Support observability and auditability for AI workflows including logging, model selection tracking, tool calls, and reviewer decisions Document workflow assumptions, guardrails, escalation criteria, fallback procedures, and operational controls for AI-enabled security workflows Assess integration patterns between AI workflows and security platforms including SIEM, SOAR, EDR, threat intelligence, and case management systems

📌 AI Security Automation Engineer to develop and operationalize AI-assisted cybersecurity workflows using agentic AI, LLMs, and security operations processes (Regina)
🏢 S.i. Systems
📍 Regina