Cyber - AI Cloud Security Engineer - Manager

Deloitte is seeking an AI Cloud Security Engineer, Manager to lead the design, implementation, and security of artificial intelligence (AI)-enabled products, platforms, and cloud environments.

This engineering-focused Manager role combines AI security architecture, AI Zero Trust, secure AI software development, cloud security engineering, and AI-enabled vulnerability discovery and remediation.

You will lead technical delivery for complex client programs, apply hands-on software engineering, cybersecurity, and cloud architecture expertise, and guide teams in building resilient AI platforms with security embedded throughout the technology lifecycle.

Recruiting for this role ends on 12/31/2026.

Work you'll do

As an AI Cloud Security Engineer, Manager on the Cyber and Cloud Security team, you will be responsible for:


* Leading the design of secure architectures for generative AI, agentic AI, retrieval-augmented generation (RAG), model serving, and AI-enabled enterprise applications; defining security boundaries and AI Zero Trust controls across models, agents, tools, application programming interfaces (APIs), data, cloud workloads, development pipelines, and runtime environments


* Establishing and implementing security practices across the AI software development lifecycle, including threat modeling, security gates, model and prompt versioning, evaluation datasets, approval workflows, release criteria, and testing for prompt injection, data leakage, unsafe tool use, model abuse, and policy violations


* Leading the design and implementation of secure AI workloads across Amazon Web Services (AWS), Microsoft Azure, Google Cloud, and hybrid environments, including cloud landing zones, network isolation, private connectivity, logging, encryption, key management, data protection, containers, serverless workloads, Kubernetes, and infrastructure-as-code controls


* Directing AI-assisted vulnerability and threat management capabilities that identify, analyze, prioritize, test, and remediate issues across code, applications, APIs, cloud configurations, infrastructure, dependencies, containers, and AI workloads; establishing human approval and validation before high-impact remediation is deployed


* Designing and building production AI security applications and platforms using full-stack engineering, including user experiences, APIs, backend services, microservices, event-driven workflows, RAG, model integrations, observability, and automated testing


* Leading client discovery, architecture sessions, technical workshops, design reviews, program delivery, production deployment, and operational handoff; managing technical workstreams, mentoring engineers, and creating reusable reference architectures, standards, playbooks, and accelerators

A successful candidate would possess these skills:


* Ability to work independently and collaborate as part of a team


* Effective written and verbal communication skills


* Metic...