Senior Technical Lead AI Database Security

About the Team

Security is fundamental to data management in enterprises. As Oracle AI Database brings AI to the data ,AI agents gain broader autonomy and connectivity, risks from prompt/data injection, excessive agency with over‑privileged access, increase significantly. The Oracle Database Security group is building the next generation data security platform in the Oracle AI Database. It delivers SQL-based, fine-grained access control at the row, column, and cell levels, enforced based on end-user identity and authorization.

It secures AI-based agentic applications, analytics tools, and enterprise workloads.

• Lead design and development of the new data security platform, integrate the platform with identity management and database application frameworks
• Own end‑to‑end architecture spanning the database kernel through middleware and identity services;
• Partner across Oracle’s RDBMS, Applications, Analytics, and SaaS teams to deliver integrated solutions
• Establish and enforce security design guidelines for database and application teams; lead design/architecture reviews and threat modeling for AI/agentic scenarios.
• Champion a culture of innovation, rigorous testing, and continuous improvement.

• 10+ years building large‑scale system software (databases, OS, distributed systems, application servers, or cloud services).
• Deep expertise in secure system design for performance, scalability, high availability, and operational manageability.
• Strong command of security fundamentals: authentication/authorization, applied cryptography, network and transport security, protocols, and enterprise security practices.
• System‑level design and programming on UNIX/Linux: memory management, concurrency control, caching, networking/RPC, and distributed systems.
• Solid understanding of major RDBMS internals and security features; fluent in SQL and database access patterns.
• Strong C/C++; or Java systems programming; familiarity with PL/SQL, JSON
• Excellent problem solving, design communication, and cross‑functional collaboration skills.
• Master’s degree in computer science/engineering or equivalent experience preferred.

• Practical understanding of LLMs and GenAI system architectures: prompt processing, context windows, embeddings/vector stores, RAG, tool use/function calling, and orchestration.
• Experience securing agentic applications: least‑privilege policy design for agents/tools, data segmentation and masking for prompts and retrieval, prompt‑injection and data‑exfiltration defenses, provenance/lineage, rate‑limiting and abuse detection, and red‑team/testing methodologies.
• Familiarity with the Model Context Protocol (MCP) and similar agent/tool interoperability standards; ability to design secure policy and identity boundaries for multi‑tool, multi‑service agent ecosystems.
• Knowledge of AI safety and compliance controls: PII/PHI protection, privacy‑preserving retrieval, consent and purpose limitation, auditability, and data residency.
• Understanding of secure integration patterns between agents, identity platforms, and data planes (e.g., token exchange, scoped credentials, just‑in‑time access, policy decision points/enforcement points).
• Awareness of emerging frameworks/standards for agent orchestration and secure plugin/tool ecosystems. If leveraging external tools or frameworks, ensure alignment with Oracle security, privacy, and compliance guidelines.

• Delivered enterprise security platforms or database security features from concept through GA and sustained operations.
• Experience with cloud security services on OCI or other public clouds; building high‑throughput, low‑latency services with strong isolation guarantees.
• Familiarity with application frameworks for Java, Python and .NET, security integration points and middleware security: 3‑tier architectures, identity and access management, and policy management systems.
• Success leading cross‑org initiatives, influencing design through clear threat models, and driving measurable security outcomes.