Senior Cloud & AI Security Enablement Engineer

Salary: £61,000 - 101,000 per year

Requirements:

• Experience in machine learning engineering.
• Strong experience in cloud security engineering, application security, security architecture, DevSecOps, or security automation.
• Hands-on experience with at least one major cloud platform, such as AWS or Azure.
• Practical knowledge of IAM, logging, encryption, secrets management, network security, storage security, vulnerability management, and secure CI/CD.
• Experience with infrastructure-as-code and cloud security tooling such as CSPM, CNAPP, IaC scanning, SAST, SCA, secrets scanning, or policy-as-code.
• Ability to translate security standards and architecture requirements into practical implementation patterns.
• Familiarity with generative AI, LLM-enabled applications, AI-assisted development, or AI security risks.
• Strong scripting, automation, workflow design, or tooling integration experience.
• Excellent written and verbal communication skills, including the ability to create clear security guidance for engineering teams.
• Desirable: Experience building cloud security guardrails, landing zone controls, reusable modules, or automated remediation workflows.
• Desirable: Experience supporting regulated environments or environments with strict customer, contractual, or compliance obligations.
• Desirable: Familiarity with AI security guidance such as the NIST AI Risk Management Framework, NIST Generative AI Profile, OWASP Top 10 for LLM Applications, or Cloud Security Alliance AI security guidance.
• Desirable: Experience with RAG architecture, AI agents, vector databases, AI APIs, prompt engineering, or AI application threat modelling.
• Desirable: Experience building security knowledge assistants, prompt libraries, AI-assisted review workflows, or security automation.

Responsibilities:

• Build and maintain reusable cloud security guardrails for identity, logging, encryption, network segmentation, secrets management, storage, workloads, containers, serverless services, and data protection.
• Translate security architecture standards into deployable cloud patterns, reference implementations, templates, and engineering-ready requirements.
• Partner with cloud, platform, DevOps, and product engineering teams to embed security controls into cloud landing zones, CI/CD pipelines, infrastructure-as-code workflows, and operational processes.
• Support the implementation and tuning of CSPM, CNAPP, cloud workload protection, IaC scanning, secrets scanning, and related cloud security tools.
• Develop policy-as-code and control-as-code mechanisms to prevent, detect, and report common cloud misconfigurations.
• Support cloud-native vulnerability and misconfiguration remediation with prioritization logic, remediation guidance, and reusable fix patterns.
• Establish cloud security metrics and dashboards covering control adoption, misconfiguration trends, remediation progress, recurring issues, and exception patterns.
• Design and maintain AI-assisted workflows for security intake triage, threat model drafting, architecture review summaries, control mapping, remediation guidance, and risk statement generation.
• Build prompt libraries, review rubrics, validation steps, and human-in-the-loop processes for approved AI use within Information Security.
• Identify repetitive BISO, AppSec, and Security Architecture tasks that can be safely accelerated through AI-assisted processes.
• Partner with GRC, Legal, Privacy, and security leadership to ensure AI-assisted security workflows are auditable, explainable, and aligned with internal risk expectations.
• Measure the effectiveness of AI-assisted workflows, including time saved, consistency improvements, review quality, and reduction in repeat manual work.
• Define secure design patterns for AI-enabled applications, including LLM-based features, retrieval-augmented generation, AI agents, AI APIs, copilots, and automation workflows.
• Establish cloud security requirements for AI workloads, including identity, secrets, data storage, network access, observability, workload isolation, and third-party AI service integrations, in partnership with Security Architecture and AppSec.
• Support AI application threat modelling and risk reviews in partnership with BISO/AppSec.
• Create developer-facing guidance for safe use of AI coding assistants, AI APIs, data ingestion, vector stores, model outputs, and AI-generated code in partnership with BISO/AppSec.
• Convert recurring BISO/AppSec and Security Architecture questions into reusable guidance, decision trees, approved patterns, checklists, and self-service workflows.
• Build lightweight intake and routing mechanisms to determine when a request needs BISO review, AppSec review, architecture review, GRC input, or engineering remediation.
• Create and maintain a library of approved cloud and AI security patterns for product and engineering teams.
• Help reduce one-off security consultations by embedding approved security decisions into tooling, templates, and standard delivery workflows.

Technologies:

• Agentic AI
• AI
• AI Agents
• AWS
• Azure
• CI/CD
• Cloud
• DevSecOps
• DevOps
• IAM
• Support
• LLM
• Machine Learning
• Network
• OWASP
• RAG
• Security
• Serverless

More:

We are LexisNexis Intellectual Property Solutions (LNIP), a global leader in patent intelligence serving businesses, law firms, universities, and government agencies. Our mission is to help the innovation community make better decisions faster by combining trusted patent data with analytics, AI-powered insights, and purpose-built workflows. Protégé in PatentSight is our next-generation agentic AI assistant for strategic patent analysis, using natural-language questions to surface structured insights grounded in trusted data and established metrics. In this senior role, you will provide hands-on cloud security engineering and enable secure, effective AI use across Information Security and product engineering. You will work across Security Architecture, BISO/Application Security, Cloud/Platform Engineering, and GRC, helping turn recurring security requirements into reusable guardrails, automated controls, AI-assisted workflows, secure design patterns, and developer enablement materials. We support work-life balance and offer flexible working hours, wellbeing initiatives, shared parental leave, study assistance, sabbaticals, holiday allowance, life assurance, a contributory pension, share options, optional dental insurance, an Employee Assistance Programme, employee resource groups, learning and development resources, and employee discounts. Benefits may vary by country. We are an equal opportunity employer and are committed to a fair and accessible hiring process.

last updated 39 week of 2026