Senior Information Cloud Security Engineer

Practice Group / Department: IT Security - Operations and Risk Job Description Norton Rose Fulbright is a global law firm with more than 3,000 lawyers advising clients across locations in the United States, Europe, Canada, Latin America, Asia, Australia, Africa and the Middle East. We provide a full scope of legal services to the world's preeminent corporations and financial institutions. Our vision is to be a world class business, profitable, ambitious, cooperative and considerate, supporting our clients and people through our global business principles of Quality, Unity and Integrity. We apply our business principles to all our activities world-wide. They describe our culture and personality both internally and externally, the way we work and what we stand for.

The Role The Senior Information Security Engineer is a senior technical role within the Global Information Security function, focused on securing cloud platforms, cloud-native services, artificial intelligence solutions, and the identities, data, applications, and integrations that support them. The role works across Azure, GCP, SaaS, AI platforms, and enterprise technology to translate security requirements into practical, scalable, and supportable controls. The role combines hands on cloud security engineering with technical governance. The successful candidate will lead cloud and AI security assessments, define secure architecture patterns, improve posture and monitoring, investigate complex security issues, automate control validation, and provide clear risk-based recommendations to technical and senior stakeholders.

Key Responsibilities Cloud Platform, Identity & Workload Security Define and continuously improve security controls and reference patterns across Azure, AWS, cloud-native services, SaaS platforms, containers, serverless workloads, virtual machines, storage, databases, APIs, and supporting network services.

Assess cloud architectures and configurations for identity, network exposure, encryption, secrets management, key management, logging, resilience, data protection, and secure administrative access.

Lead technical investigations involving cloud identities, service principals, managed identities, workload identities, API permissions, privileged access, exposed services, misconfiguration, and suspicious cloud activity.

Embed security into cloud engineering and delivery practices by working with architects, platform teams, developers, and service owners to apply secure-by-design guardrails throughout the technology lifecycle.

Cloud Posture, Exposure & Security Assurance Own and improve cloud security posture and workload-protection processes, including platform onboarding, control baselining, finding validation, risk prioritization, remediation tracking, exception handling, and integration with governance processes.

Support vulnerability and exposure management across internet-facing assets, cloud workloads, applications, containers, and SaaS services using available posture, vulnerability, attack surface, and threat data.

Perform security reviews of cloud solutions, integrations, APIs, infrastructure as code, and technology changes, with emphasis on least privilege, segmentation, encryption, logging, auditability, secure configuration, and operational ownership.

AI Security, Automation & Engineering Define and apply security requirements for enterprise AI, generative AI, copilots, agents, machine learning services, and AI enabled SaaS solutions, including data access, prompt and response handling, model or service permissions, identity, logging, retention, and human oversight.

Assess AI specific threats and control gaps, including prompt injection, sensitive data leakage, insecure agent actions, excessive permissions, unapproved integrations, third party model risk, and inadequate monitoring; translate findings into proportionate safeguards.

Build automation and proof of concept solutions using PowerShell, Python, KQL, APIs, policy as code, infrastructure as code, cloud native functions, and workflow technologies, and mature successful concepts into governed, supportable services.

Monitoring, Governance, Reporting & Leadership Define security telemetry and detection requirements for cloud and AI services, and work with monitoring teams to ensure relevant identity, administrative, data access, workload, and application activity is available for investigation and response.

Develop and maintain cloud and AI security standards, architecture patterns, technical procedures, assessment methodologies, runbooks, and control validation processes.

Provide technical input to security incidents, threat led investigations, assurance reviews, audits, client inquiries, and risk assessments involving cloud or AI services.

Create meaningful KPIs, dashboards, technical reports, and executive ready summaries that communicate cloud and AI risk exposure, control effectiveness, remediation progress, and operational trends.

Provide technical leadership, coaching, and knowledge transfer; act as an escalation point for complex cloud and AI security issues across global technology teams.

Maintain awareness of emerging cloud capabilities, AI attack techniques, regulatory expectations, and industry good practice; recommend proportionate improvements and manage assigned initiatives through design, implementation, documentation, handover, and operational acceptance.

Key Objectives Ensure cloud platforms, cloud native services, SaaS applications, and AI solutions are securely designed, configured, monitored, and continuously improved.

Provide senior technical ownership and escalation support for cloud security posture, workload protection, identity, data protection, application security, and AI related security risks.

Advance the Firm's cloud and AI security capabilities through reusable guardrails, automated assurance, reliable telemetry, actionable reporting, and supportable operational processes.

Contribute to technical, procedural, and governance improvements aligned with the Information Security Management System (ISMS), cloud control frameworks, and the Firm's AI governance requirements.

Skills and Experience Required Essential At least 5 years of relevant experience in cloud security, security engineering, cloud architecture, DevSecOps, or a closely related technical discipline.

Recent hands on experience securing public cloud environments such as Azure and GCP in a large or complex enterprise.

Strong knowledge of cloud identity and access management, workload identities, privileged access, federation, conditional access, service principals, managed identities, and least privilege design.

Demonstrable experience assessing cloud architectures and configurations across compute, storage, databases, networking, containers, serverless technologies, APIs, key management, secrets management, and logging.

Practical experience with cloud security posture management, cloud workload protection, vulnerability management, attack surface management, and risk based remediation.

Experience defining or evaluating security controls for generative AI, enterprise copilots, AI agents, machine learning platforms, or AI enabled SaaS solutions.

Understanding of AI specific security risks, including prompt injection, sensitive data exposure, insecure tool or agent actions, excessive permissions, third party model risk, and insufficient monitoring or governance.

Ability to automate security processes and control validation using PowerShell, Python, KQL, APIs, policy as code, infrastructure as code, cloud native functions, or comparable technologies.

Experience reviewing cloud solution designs and integrations for authentication, authorization, network controls, encryption, data protection, logging, monitoring, resilience, and secure operational ownership.

Ability to troubleshoot complex technical issues across cloud, identity, application, API, network, data, and security monitoring layers.

Experience producing clear architecture guidance, technical standards, operational procedures, dashboards, risk assessments, and reports for technical and non technical audiences.

Working knowledge of relevant frameworks and practices such as ISO27001, NIST, CIS Benchmarks, cloud security control frameworks, secure development practices, and emerging AI risk management guidance.

Strong stakeholder management and communication skills, with the ability to challenge constructively and translate complex cloud and AI security issues into business risk.

Ability to work independently, manage competing priorities, and lead defined initiatives through to completion in a global, matrixed environment.

Desirable Relevant cloud security, cloud architecture, DevSecOps, or AI security certifications.

Experience with multi cloud environments, cloud native security tooling, CI/CD security, infrastructure as code scanning, container security, or Kubernetes security.

Experience with enterprise AI governance, AI red teaming, AI threat modelling, secure AI architecture, or AI security testing.

Experience working in a regulated professional services environment with strong confidentiality, data protection, and client security requirements.

Experience transitioning proofs of concept into production services using formal architecture, change management, documentation, and operational acceptance processes.

Diversity, Equity and Inclusion To attract the best people, we strive to create a diverse and inclusive environment where everyone can bring their whole selves to work, have a sense of belonging . click apply for full job details