Cyber Manager: AI Data Security

Deloitte • Jersey City, NJ

5d • $134,500 - $265,100

About The Position

As a Manager: AI Data Security in Deloitte's Cyber for AI team, you will lead client engagements focused on securing how enterprise data is ingested, transformed, retrieved, and used by RAG and agentic systems. You will translate business and risk objectives into target architectures, 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 develop repeatable delivery assets.

The Cyber for AI team helps organizations secure generative AI and agentic systems from design through production. It combines AI engineering and cybersecurity skills across identity, data, infrastructure, application security, and operations. The Data capability focuses on discovering, classifying, retrieving, transforming, and protecting enterprise data across RAG pipelines, vector stores, model context, and agent memory.

The role involves client-facing leadership and requires an average of 20–50% travel, depending on the work, clients, and industries served. Recruiting for this role ends on 05/31/2027.

Requirements

• At least 6 years of combined cybersecurity and AI architecture and engineering experience, including leading production generative AI or agentic implementations across models, orchestration, identity, data, and infrastructure.
• Experience designing and implementing data security controls in AWS, Azure, and/or Google Cloud, with experience with data security patterns in the other two platforms.
• Experience architecting and implementing secure RAG and agentic data platforms across structured and unstructured enterprise sources.
• Experience with vector, search, and data platforms, including tenant isolation, document- or row-level entitlements, metadata filtering, and identity-aware retrieval.
• Experience integrating classification, catalog, lineage, fine-grained access, encryption, key management, tokenization, redaction, and data loss prevention technologies into production data paths.
• Experience reviewing or developing Python and SQL pipelines, access-control logic, validation tooling, and CI/CD integrations.
• Experience leading client-facing technology or cyber engagements with responsibility for scope, teams, timelines, quality, and executive stakeholders.
• Bachelor’s degree in Computer Science, Engineering, Information Technology, Cybersecurity, or a related field; equivalent demonstrated experience is also accepted.
• Ability to travel 20–50% on average, based on work and client or industry needs.
• Ability to work independently and collaboratively as part of a team.
• Effective written and verbal communication skills.
• Meticulous attention to detail and quality of work product.
• Ability to build and sustain professional relationships.
• Ability to lead projects or workstreams.
• Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment.
• Strong interpersonal skills and professional demeanor.
• Ability to meet deadlines.
• Ability to mentor and provide clear guidance to others.

Nice To Haves

• Experience with managed AI services and self-hosted or open-weight AI platforms.
• Experience with AI threat modeling, red teaming, security evaluations, secure AI development practices, or AI-specific monitoring.
• Experience building reusable technical assets, delivery methods, or automation for client engagements.
• Experience with machine learning tools and frameworks such as PyTorch, TensorFlow, or MLflow.
• Experience with AI data services such as Amazon Bedrock Knowledge Bases, Microsoft Foundry with Azure AI Search, Google Vertex AI RAG Engine, or Databricks AI capabilities.
• Experience with enterprise data security and governance platforms such as Microsoft Purview, Amazon Macie and Lake Formation, Google Sensitive Data Protection, BigID, Collibra, Immuta, or Privacera.
• Preferred certifications: CISSP, CCSP, CDPSE, AWS/Azure/GCP cloud certifications, Databricks and/or Snowflake certifications, or data engineering certifications.

Responsibilities

• Lead AI data security assessments, architecture workshops, and implementation programs for RAG and agentic systems.
• Translate data use cases and risk requirements into target architectures spanning sources, pipelines, vector stores, retrieval, context, outputs, and memory.
• Participate directly in design reviews, entitlement and metadata decisions, critical pipeline and policy reviews, and resolution of high-risk technical issues.
• Manage engagement scope, teams, milestones, quality, and client expectations while maintaining a clear path from design to production adoption.
• Coordinate data security dependencies across identity, cloud, network, AI engineering, application security, privacy, and operations teams.
• Shape solutions during pursuits through workshops, demonstrations, proofs of concept, estimates, and delivery plans.
• Develop reusable secure RAG patterns, validation tooling, and delivery methods.
• Coach practitioners on engineering quality.

Benefits

• Employees are offered a broad range of benefits.
• Eligible employees may participate in a discretionary annual incentive program, subject to program rules and applicable performance factors.
• Opportunities for professional development, including on-the-job learning, formal development programs, leadership opportunities, and mentorship.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager