Managing Consultant – AI Security & Assurance

Overview

As an AI Security specialist at PA, you help enterprise clients design, build, and deploy secure AI solutions in regulated environments. You embed security into the AI development lifecycle to ensure resilient, compliant systems. You act as a trusted advisor and technical architect, guiding clients through rapid AI evolution and emerging threats. This role offers the chance to shape secure AI architectures across high-stakes domains and to work with cross-functional teams to deliver lasting impact.

Pay / Benefits

• Private healthcare for you and family
• 25 days annual leave (+ 0.5 day on Christmas Eve)
• Generous pension scheme
• Annual performance-based bonus
• Cycle to work and other tax-efficient benefits
• Community and charity initiatives

Responsibilities

• Serve as a trusted advisor and technical architect for AI security initiatives
• Lead technical discussions and structure client challenges around AI security risks
• Assist clients in designing and implementing AI systems with secure-by-design principles
• Identify and mitigate emerging AI threats (e.g., prompt injection, data leakage)
• Embed security controls into the AI build lifecycle (DevSecOps for AI/MLSecOps)
• Communicate complex security risks to senior stakeholders (CISOs, Enterprise Architects)
• Contribute to delivery of AI security capabilities and continuous-learning in fast-evolving tech
• Support regulated-environment engagements translating GDPR, EU AI Act, HIPAA, SEC/FINRA into safeguards

Key requirements

• Demonstrable understanding of AI/ML architectures (LLMs, generative AI, predictive models)
• Experience with secure AI build processes and data pipeline security
• Knowledge of data protection, DLP, and data egress controls in AI contexts
• Familiarity with AI risk frameworks and threat vectors (OWASP Top 10 for LLMs, NIST AI RMF)
• Ability to navigate regulated environments and translate requirements into safeguards
• Proven client-facing delivery and ability to communicate risks to senior stakeholders
• Continuous-learning mindset with adaptability to evaluate emerging AI technologies
• Preferred certifications in security or cloud (e.g., CISSP, CCSP, AWS/Azure/GCP Security) and AI/ML security coursework

• Strong communication with senior stakeholders
• Adaptability and continuous learning
• Collaborative, cross-functional mindset
• AI/ML architectures (LLMs, generative AI, predictive models)
• DevSecOps for AI/MLSecOps integration
• Data protection and DLP in AI pipelines

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