Cyber Manager: AI Data Security

As a Manager: AI Data Security in Deloitte's Cyber for AI team, you will lead client engagements that secure how enterprise data is ingested, transformed, retrieved, and used by RAG and agentic systems.

You will translate business and risk objectives into target architecture, remain directly involved in critical design and engineering decisions, and guide teams from assessment through implementation.

You will also shape solutions during pursuits and help build repeatable delivery assets.

Recruiting for this role ends on 05/31/2027.

Work you'll do

As a Manager: AI Data Security, you will be responsible for:


* Leading AI data security assessments, architecture workshops, and implementation programs for RAG and agentic systems.


* Translating data use cases and risk requirements into target architectures spanning sources, pipelines, vector stores, retrieval, context, outputs, and memory.


* Remaining directly involved in design reviews, entitlement and metadata decisions, critical pipeline and policy reviews, and resolution of high-risk technical issues.


* Managing engagement scope, teams, milestones, quality, and client expectations while maintaining a clear path from design to production adoption.


* Coordinating data security dependencies across identity, cloud, network, AI engineering, application security, privacy, and operations teams.


* Shaping solutions during pursuits through workshops, demonstrations, proofs of concept, estimates, and delivery plans.


* Developing reusable secure RAG patterns, validation tooling, and delivery methods.


* Coaching practitioners on engineering quality.

The Team

Deloitte's Cyber for AI team helps organizations secure generative AI and agentic systems from design through production.

The team brings together AI engineering and cyber skills across identity, data, infrastructure, application security, and operations.

We work with clients to make security controls part of the platform and delivery lifecycle, so teams can move from experiments to production without creating unmanaged access, data, or infrastructure risk.

Within the team, our Data capability focuses on how enterprise data is discovered, classified, retrieved, transformed, and protected across RAG pipelines, vector stores, model context, and agent memory.

Qualifications

6+ years of combined cybersecurity and AI architecture & engineering experience, including leading production generative AI or agentic implementations across models, orchestration, identity, data, and infrastructure.

Required Experience:


* Designing and implementing data security controls in either AWS, Azure, and/or Google Cloud with experience with data security patterns in the other two platforms.


* Architecting and implementing secure RAG and agentic data platforms across structured and unstructured enterprise sources.


* Vector, search, and data platforms including tenant isolation, document- or row-level entitlements, ...