Systems Engineer II- Detection Engineering

Essential:

· Engineering & Development Expertise: Demonstrable understanding of software development lifecycles, with hands-on exposure to programming and building production-grade solutions.

· Secure & Test-Driven Engineering: Experience applying secure coding practices and test-driven development approaches within an engineering or security context.

· Core Cyber Defence Technology: Practical exposure to security platforms (e.g., Security Information and Event Management (SIEM), Endpoint Detection and Response (EDR)) and their role in detection engineering.

· Detection Engineering Fundamentals: Understanding of how custom detection rules, alerts, and telemetry are designed, tested, and implemented to identify malicious activity at scale. Able to reduce noise without impacting visibility, and to sustain detection quality over time,

· Continuous Learning & Curiosity: Evidence of strong curiosity and commitment to professional development, staying current with evolving threats and technologies.

· Collaboration & Inclusion: Ability to work effectively within diverse, cross-functional teams, contributing to an inclusive and supportive engineering environment.

· Pragmatic Problem Solving: Solid critical thinking capability, with the ability to break down complex problems and deliver practical, scalable solutions.

Desirable:

· Exposure to core technology platforms and retail technology environments.

· Understanding of cloud and container security principles.

· Experience in security evaluation, functionality testing, and validation of controls.

· Familiarity with Applied Artificial Intelligence (AI) concepts in cyber defence.

· Experience using tools such as Github, Jira, Zendesk, and xMatters for engineering workflow and operational collaboration.

· Experience with a querying language such as SPL, KQL, SQL, etc. In a Security Environment.

· Strong communication and influencing skills within technical teams.

· Awareness of product methodologies and agile delivery approaches.

· Exposure to technical security architecture concepts and data analytics for security.

Understanding of responsible AI governance and compliance principles.