About the Opportunity Job Type: Permanent Application Deadline: 31 May 2026 We’re proud to have been helping our clients build better financial futures for over 50 years. How have we achieved this? By working together - and supporting each other - all over the world. So, join our team and feel like you’re part of something bigger. About your team The Cyber Defence Operations team delivers global detection and response capabilities to protect Fidelity’s systems, data, and clients. The team operates across regions to identify, investigate, and respond to cyber threats while continuously improving security controls and operational effectiveness. Detection Engineering & Automation is a core capability within Cyber Defence Operations, responsible for building, maintaining, and evolving detection logic, automation workflows, and security tooling that enable scalable and effective cyber defence. About your role As Detection Engineering & Automation Manager, you will lead the development and delivery of detection and automation capabilities across the organisation. You will be accountable for ensuring detection logic, automation workflows, and security tooling are engineered to a high standard, aligned to risk priorities, and delivered consistently across environments. A key focus of this role is driving the transition to a Detection as Code model, where detection capabilities are developed, tested, and deployed through controlled engineering pipelines. You will establish DevSecOps practices within cyber operations, ensuring detection and automation are version-controlled, validated, and deployed in a repeatable and scalable way. You will operate across both delivery and capability development, improving engineering standards, increasing automation, and enabling Cyber Operations to respond effectively to evolving threats. Key responsibilities Lead and manage a global Detection Engineering & Automation capability, ensuring consistent and high-quality delivery Own the development lifecycle of detection use cases, from design and testing through to deployment and optimisation Drive adoption of Detection as Code, ensuring detection logic is version-controlled, testable, and reusable Design and implement CI/CD pipelines for detection and automation, enabling controlled and scalable deployment Establish engineering standards including code quality, testing, release management, and change governance Own delivery planning and prioritisation, aligning engineering output to risk, threat intelligence, and operational needs Improve detection coverage, alert quality, and operational effectiveness through continuous improvement Oversee performance, optimisation, and integration of security tooling (e.g. SIEM, SOAR, endpoint and email security platforms) Collaborate with Security Operations, Incident Response, and Threat Intelligence to ensure detection capabilities are actionable and effective Partner with enterprise engineering teams to align detection pipelines with broader DevSecOps and platform standards Lead, mentor, and develop engineers within the team, supporting capability growth and progression About you You are an experienced detection engineering leader with a strong technical background and a structured approach to delivery. You are comfortable leading teams, improving engineering practices, and working across multiple stakeholders to deliver outcomes. You bring an engineering mindset to cyber security, focusing on scalability, quality, and automation. You are motivated by improving how things are built and delivered, not just what is delivered. Essential skills and experience Experience leading or managing detection engineering, security engineering, or automation capabilities Strong hands-on experience with SIEM platforms and detection use case development Experience implementing Detection as Code or infrastructure-as-code approaches Experience building or working with CI/CD pipelines (e.g. Azure DevOps, GitHub Actions, Jenkins) Strong scripting or programming capability (e.g. Python, PowerShell, or similar) Experience working in cloud environments (e.g. Azure, AWS) and integrating telemetry into detection platforms Understanding of software engineering practices including version control, testing, and release management