USI- Cyber- DT&P -Data Protection - AI Security Consultant - L35

AI Security Senior Consultant, Data
As an AI Security Consultant specializing in Data in Deloitte Cyber's Cyber for AI practice, you will own technical workstreams that secure how enterprise data is ingested, transformed, retrieved and used by RAG and agentic systems. You will combine client advisory with hands-on engineering, turning requirements into architectures, integrations and production controls. You will guide junior p
ractitioners, lead demonstrations and help estimate delivery work.
Work you'll do
As an AI Security Consultant on the Data team, you will be responsible for:-
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.
Remain hands-on through design reviews, entitlement and metadata decisions, critical pipeline or policy review, 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, and coach practitioners on engineering quality.
A successful candidate would possess these skills:
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Ability to lead multidisciplinary teams while staying close to the architecture, engineering and technical risks.
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Strong judgment in balancing technical quality, delivery scope, timelines and client priorities.
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Ability to communicate credibly with engineers, security leaders and executives, and turn complex issues into clear       decisions.
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A consistent record of mentoring practitioners, providing direct feedback and building trusted client relationships.
The team
Deloitte Cyber's Cyber for AI practice 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 practice, the 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
Required:
Bachelor's degree in Computer Science, Engineering, Information Technology, Cybersecurity or a related field; alternatively, equivalent demonstrated experience.
3+ years of combined cybersecurity and AI engineering experience, including hands-on production work in both domains.
Demonstrated experience architecting and leading production generative AI or agentic implementations, including technical decisions across models, orchestration, identity, data and infrastructure
Hands-on depth in AWS, Azure or Google Cloud, with working knowledge of data security patterns in the other major cloud platforms.
Advanced hands-on experience architecting and implementing secure RAG and agentic data platforms across structured and unstructured enterprise sources.
Deep 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 DLP technologies into production data paths.
Ability to review and, when needed, develop Python and SQL pipelines, access-control logic, validation tooling and CI/CD integrations.
Prior consulting experience leading client-facing technology or cyber engagements, including scope, teams, timelines, quality and executive communication.
Ability to travel 25% to 50%, on average, based on the work you do and the clients and engagements you serve.
Preferred:
Experience across both 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 that can scale across client engagements.
Familiarity with the broader machine learning lifecycle 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, Databricks AI capabilities or comparable platforms.
Experience with enterprise data security and governance platforms such as Microsoft Purview, Amazon Macie and Lake Formation, Google Sensitive Data Protection, BigID, Collibra, Immuta, Privacera or comparable technologies.
Relevant certifications such as CISSP, CCSP, CDPSE, or cloud, Databricks, Snowflake and data engineering certifications
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