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Job Description
You will manage and automate two core security capabilities: data protection (classification and data loss prevention) and the workflow automation behind our vulnerability and exposure management programme, wiring security findings into ticketing workflows (e.g. Jira) so that risks are tracked, findings reach their owners, and evidence collects itself.
You will leverage advanced automation and frontier AI models with the validation discipline that keeps AI-assisted work trustworthy and auditable. This is a hands-on role suited to a fresh graduate or early-career engineer, with structured mentoring and work that lands in front of auditors, committees and system owners.
Responsibilities
- Data Protection Management: Manage the day-to-day operation of our implemented data classification and data loss prevention (DLP) capability (e.g. Microsoft Purview): maintain and tune sensitivity labels (including auto-labeling policies) and DLP policies as the business changes, verify that labels enforce the intended controls, investigate policy hits and tune out false positives, and automate reporting on label coverage and policy hits.
- Workflow and Integration Automation: Design, build and operate ticketing workflows (e.g. Jira / Jira Service Management) for risk acceptance, security exceptions, remediation tracking and DLP follow-up, including service-level agreement (SLA) clocks and dashboards; automate the flow of security findings (e.g. from the vulnerability and data-protection platforms) into those workflows with asset owner and criticality enrichment, using APIs and scripting.
- AI Automation for Exposure Management (CTEM): Build the automation and AI-assisted tooling behind the organisation's Continuous Threat Exposure Management (CTEM) programme in support of the vulnerability management owner: automated triage aids, prioritisation data feeds (e.g. Known Exploited Vulnerabilities (KEV) catalogue, Exploit Prediction Scoring System (EPSS), asset criticality), coverage reporting and remediation dashboards across our security tooling (e.g. Tenable), so the operations cycle runs on tooling rather than spreadsheets.
- Compliance Evidence Automation: Build scripted pipelines that collect and check control evidence (e.g. access reviews, patch and configuration compliance, label coverage) in support of certification and audit cycles (e.g. ISO 27001, SOC 2), with automated checks that raise a ticket when a control drifts.
- Security Requirements and Testing: Help translate security needs into testable requirements and acceptance criteria for internal systems and integrations, and test delivered capability against them.
- AI-Assisted Security Operations: Leverage frontier AI models and advanced automation to accelerate analysis, integration code and workflow efficiency, validating AI outputs before action and handling operational data according to its classification.
Requirements
- Degree in Cybersecurity, Computer Science, Information Systems, or an equivalent technical field of study.
- 0 to 3 years of experience in security operations, IT or software engineering
- Proficiency in scripting (Python or PowerShell preferred) and comfort with REST APIs, JSON and Git, demonstrated through work, internship, academic or personal projects.
- Strong foundation in core security concepts (e.g. the CIA triad, common vulnerability classes, CVSS scoring and its limitations) and a genuine interest in data protection and security automation.
- Experience with frontier AI models (e.g. Anthropic, OpenAI, or similar) for code or analysis, with strong output-validation habits.
- Meticulous with data, process and documentation; this role touches audit evidence, sensitive-data controls and risk registers, where accuracy matters more than speed.
- Clear written and verbal communication skills for cross-team coordination.
- Operationally focused mindset with the ability to thrive in a dynamic, fast-paced environment.
Additional Experience/Knowledge
- Familiarity with Microsoft 365 security and compliance tooling (e.g. Microsoft Purview, sensitivity labels, DLP), the Microsoft Graph API, or data protection regulation basics (e.g. PDPA).
- Exposure to an enterprise vulnerability management platform (e.g. Tenable), Jira / Jira Service Management (even as a user), or a public cloud platform (Azure, AWS or GCP).
- Query and data skills (SQL or KQL), or Linux fundamentals.
- Participation in Capture the Flag (CTF) challenges, or entry-level certifications (e.g. ISC2 Certified in Cybersecurity, CompTIA Security+, Microsoft SC-900, cloud fundamentals).
- Internship or project experience in a security team, or work the team can look at (e.g. GitHub repositories, technical write-ups).
