Cyber - Senior Consultant, AI Data Security
About The Position
As a Senior Consultant in Deloitte's Cyber for AI team, you will own technical workstreams that secure how enterprise data is ingested, transformed, retrieved, and used by generative AI, RAG, and other agentic systems. The role combines client advisory with hands-on engineering to translate requirements into architecture, integrations, and production controls. You will guide junior practitioners, lead demonstrations, and contribute to delivery estimates. The Data capability focuses on discovering, classifying, retrieving, transforming, and protecting enterprise data across RAG pipelines, vector stores, model context, and agent memory. Deloitte's Cyber for AI team helps organizations secure generative AI and agentic systems from design through production, integrating security controls into platforms and delivery lifecycles. Recruiting for this role ends on 05/31/2027. The position requires an average of 20% to 50% travel, depending on work and clients. Limited immigration sponsorship may be available. The estimated wage range is $105,400 to $207,800, with possible eligibility for a discretionary annual incentive. Deloitte offers a broad range of benefits and professional development opportunities.
Requirements
- 3–5+ years of combined cybersecurity and AI engineering experience, including hands-on production work in both domains.
- Experience designing, integrating, and securing production generative AI, RAG, or agentic workloads, including model, tool, and enterprise data connections.
- Experience designing and securing RAG or agentic data paths across ingestion, chunking, embeddings, vector indexing, retrieval, prompt context, outputs, and memory.
- Experience with data security patterns in AWS, Azure, or Google Cloud.
- Experience implementing vector, search, and/or data platforms such as Pinecone, Weaviate, Milvus, pgvector, OpenSearch, Elasticsearch, Azure AI Search, Vertex AI Vector Search, Databricks, or Snowflake.
- Experience with data security controls for classification, tagging, lineage, fine-grained access, metadata filtering, encryption, key management, tokenization, redaction, and DLP.
- Experience designing, building, and reviewing data pipelines using Python, SQL, Spark, Kafka, Airflow, cloud-native data services, Git, and CI/CD practices.
- Bachelor's degree in Computer Science, Engineering, Information Technology, Cybersecurity, or a related field.
- Ability to travel 20% to 50% on average, depending on work and clients.
- Ability to work independently and collaboratively, communicate effectively in writing and verbally, and produce meticulous, high-quality work.
- Ability to build and sustain professional relationships; lead projects or workstreams; manage and prioritize multiple tasks in a fast-paced environment; meet deadlines; and provide clear guidance to others.
- Strong interpersonal skills and professional demeanor.
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.
- CISSP, CCSP, CDPSE, AWS/Azure/GCP cloud certifications, Databricks or Snowflake certifications, or data engineering certifications.
Responsibilities
- Lead discovery and data-flow analysis for RAG applications, agents, vector stores, enterprise sources, and downstream outputs.
- Design secure data architectures for ingestion, transformation, embeddings, indexes, retrieval, context assembly, caching, and memory.
- Lead integrations with classification, catalog, lineage, data loss prevention, encryption, secrets management, and fine-grained authorization services.
- Engineer entitlement-aware retrieval and metadata-filtering patterns across structured and unstructured data sources.
- Plan and execute control testing for tenant isolation, access filtering, data leakage, and pipeline reliability.
- Own a data security workstream, manage dependencies and milestones, and provide day-to-day guidance to consultants.
- Lead technical demonstrations and prototypes.
- Contribute architecture, effort, and estimation inputs to pursuits.
Benefits
- Broad range of employee benefits
- Professional development opportunities, including on-the-job learning, formal development programs, mentorship, and leadership opportunities
- Potential eligibility for a discretionary annual incentive program
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What This Job Offers
Job Type
Full-time
Career Level
Senior
