Senior Cloud & AI Security Enablement Engineer

Senior Cloud & AI Security Enablement Engineer Enthusiastic about securing cloud platforms and AI-driven solutions in a rapidly evolving technology landscape?

Do you enjoy designing security frameworks, enabling secure development practices, and partnering with engineering teams to build resilient, scalable, and compliant cloud and AI environments?

About the team:

Lexis Nexis Intellectual Property Solutions (LNIP) is the global leader in patent intelligence, bringing clarity to innovation for businesses, law firms, universities, and government agencies worldwide. Our mission is to help the innovation community make better decisions faster, with greater confidence, combining the world’s most trusted patent data with sophisticated analytics, AI-powered insights, and purpose-built workflows.

Protégé in Patent Sight is LNIP’s next-generation agentic AI assistant, purpose-built for strategic patent analysis. Protégé replaces complex filter-based workflows with natural language questions, surfacing structured, decision-ready insights grounded in trusted data and established metrics.

About the role:

We are seeking a Senior Cloud & AI Security Enablement Engineer to provide hands-on cloud security engineering capability while also enabling the secure and effective use of AI across Information Security and product engineering teams.

This role sits between Security Architecture, BISO/Application Security, Cloud/Platform Engineering, and GRC. It is designed to reduce manual workload on Security Architecture and BISO/Application Security by turning recurring security requirements into reusable cloud guardrails, automated controls, AI-assisted workflows, secure design patterns, and developer-facing enablement materials.

The successful candidate will be a practical builder and security partner who can operate cloud security controls, support secure AI adoption, and use AI to improve the speed and consistency of security delivery.

Key Responsibilities:

Cloud Security Engineering 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, Dev Ops, 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 tooling.

Develop policy-as-code and control-as-code mechanisms to prevent, detect, and report common cloud misconfigurations.

Support cloud-native vulnerability and misconfiguration remediation by providing 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.

AI Security Enablement 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, App Sec, 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.

Secure AI Application and Cloud-AI Guardrails 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…