Senior Information Cloud Security Engineer

Posted 4 Days Ago
Be an Early Applicant
2 Locations
Hybrid
Senior level
Legal Tech • Financial Services
The Role
Leads cloud and AI security engineering across Azure, AWS, GCP, SaaS, identities, workloads, data, applications, and integrations. Defines secure architecture patterns, assesses cloud and AI risks, improves security posture and monitoring, investigates complex issues, automates control validation, and develops governance standards, dashboards, reports, and remediation processes. Provides technical leadership, stakeholder guidance, coaching, and escalation support while advancing secure-by-design practices and AI security capabilities.
Summary Generated by Built In

Practice Group / Department:

IT Security - Operations and RiskJob 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.


The Team

The Global Information Security team delivers strategic and operational improvements that strengthen the Firm’s security posture. The team works across regions and technology functions to define security standards, improve visibility, manage cyber risk, and ensure that cloud and enterprise services are securely designed, implemented, monitored, and continuously improved.


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 ISO 27001, 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.

#LI-JC1 #LI-Hybrid

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, and realize their full career potential. 
Our new enabled work model allows our people to have more flexibility in the way they choose to work from both the office and a remote location, while continuing to deliver the highest standards of service. We offer a range of family friendly and inclusive employment policies and provide access to programmes and services aimed at nurturing our people’s health and overall wellbeing. Find more about Diversity, Equity and Inclusion here.

We are proud to be an equal opportunities employer and encourage applications from individuals who can complement our existing teams. We strive to create an inclusive and accessible recruitment process for all candidates. If you require any tailored adjustments or accommodations, please let us know here.

Skills Required

  • 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.
  • Experience assessing cloud architectures and configurations across compute, storage, databases, networking, containers, serverless technologies, APIs, key management, secrets management, and logging.
  • 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 architecture guidance, technical standards, operational procedures, dashboards, risk assessments, and reports for technical and non-technical audiences.
  • Working knowledge of ISO 27001, 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 translate complex cloud and AI security issues into business risk.
  • Ability to work independently, manage competing priorities, and lead defined initiatives through completion in a global, matrixed environment.
  • 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 in a regulated professional-services environment with 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.
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The Company
HQ: London
8,733 Employees

What We Do

We provide the world’s preeminent corporations and financial institutions with a full business law service. We have more than 3,500 lawyers and other legal staff based in Europe, the United States, Canada, Latin America, Asia, Australia, the Middle East and Africa. Recognized for our industry focus, we are strong across all the key industry sectors: financial institutions; energy, infrastructure and resources; consumer markets; transport; technology; and life sciences and healthcare. Through our global risk advisory group, we leverage our industry experience with our knowledge of legal, regulatory, compliance and governance issues to provide our clients with practical solutions to the legal and regulatory risks facing their businesses. Wherever we are, we operate in accordance with our global business principles of quality, unity and integrity. We aim to provide the highest possible standard of legal service in each of our offices and to maintain that level of quality at every point of contact. Norton Rose Fulbright Verein, a Swiss verein, helps coordinate the activities of Norton Rose Fulbright members but does not itself provide legal services to clients. Norton Rose Fulbright has offices in more than 50 cities worldwide, including London, Houston, New York, Toronto, Mexico City, Hong Kong, Sydney and Johannesburg. For more information, see nortonrosefulbright.com/legal-notices

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