Project Manager - Cybersecurity & AI Experience

Role Purpose Lead the end-to-end delivery of AI-enabled cybersecurity capabilities that reduce risk and improve detection, response, and resilience. You’ll coordinate cyber, data, engineering, and risk/control stakeholders to take use cases from concept to production—safely, compliantly, and with measurable outcomes. Key Responsibilities * Delivery leadership (end-to-end) * Own delivery plans, milestones, dependencies, and RAID across multiple cyber-AI workstreams. * Run delivery cadence (Agile/Hybrid), ensuring predictable execution and clear reporting to senior stakeholders. * Translate cyber priorities into deliverable backlogs and release plans (MVP → scale). * Cyber AI use cases (typical scope) * Security operations (SOC): alert triage, correlation, enrichment, prioritisation. * Threat detection: anomaly detection, UEBA-style patterns, phishing/malware classification support. * Vulnerability management: risk-based prioritisation, remediation insights. * Identity \& access: behavioural signals, privileged access monitoring. * GenAI for cyber: analyst copilots, investigation summarisation, playbook assistance (with guardrails). * Data, engineering \& platform coordination * Partner with cyber engineering, data science, and platform teams to ensure: * Data sourcing, quality, lineage, and access approvals. * Secure model deployment patterns (e.g., isolated environments, secrets management). * Monitoring for model performance, drift, and operational health. * Risk, controls \& responsible AI (critical) * Ensure alignment with information security, privacy, model risk management, and regulatory expectations. * Drive documentation and approvals: model cards, threat modelling, DPIAs (where needed), validation evidence, audit trails. * Implement guardrails for GenAI: prompt controls, data leakage prevention, human-in-the-loop, logging, and incident response. * Stakeholder management \& governance * Establish governance forums (working group/steerco), decision logs, and escalation paths. * Communicate progress in plain language: outcomes delivered, risk posture, and next steps. * Coordinate third parties/vendors where applicable and manage delivery outcomes. * Value realisation \& operational readiness * Define success metrics (e.g., reduced MTTD/MTTR, improved precision/recall, analyst time saved, fewer false positives). * Drive adoption: training, runbooks, support model, and handover to BAU operations. * Track benefits post-release and iterate based on SOC feedback and performance data. Required Skills / Experience * Proven delivery leadership for complex cyber and/or data/AI initiatives (multi-team, enterprise scale). * Strong understanding of cybersecurity operations and controls (SOC processes, incident response, detection engineering concepts). * Working knowledge of AI/ML lifecycle and MLOps/ModelOps concepts (deployment, monitoring, drift, retraining). * Experience delivering in regulated environments with strong governance and audit requirements. * Excellent stakeholder management and ability to influence across cyber, tech, and risk functions. Desirable Skills / Experience * Experience with SIEM/SOAR ecosystems and security telemetry (e.g., logs, EDR, network, IAM signals). * Familiarity with threat modelling (e.g., STRIDE), adversarial ML considerations, and secure AI patterns. * GenAI delivery experience with enterprise guardrails (RAG, red-teaming, prompt injection mitigation). Cloud security and data governance exposure.