Database System Engineer - AI Data Security (redwood Shores, Ca)

Oracle Oracle · Enterprise · Redwood City, CA +1

This role focuses on designing and developing a next-generation data security platform for Oracle's AI Database, specifically addressing the security risks associated with autonomous AI agents. The engineer will lead the architecture, integrate with identity management, and establish security guidelines, with a strong emphasis on securing agentic applications, LLMs, and GenAI systems, including prompt injection defenses, data segmentation, and least-privilege policy design.

What you'd actually do

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

Skills

Required

  • Database system and security expertise
  • Secure system design
  • Security fundamentals (authentication/authorization, cryptography, network security)
  • System-level design and programming on UNIX/Linux
  • RDBMS internals and security features
  • SQL
  • C/C++ or Java systems programming
  • LLMs and GenAI system architectures
  • Securing agentic applications
  • Model Context Protocol (MCP)
  • AI safety and compliance controls
  • Secure integration patterns for agents and data planes
  • Agent orchestration frameworks

Nice to have

  • PL/SQL
  • JSON
  • delivered enterprise security platforms
  • cloud security services
  • Java, Python and .NET application frameworks
  • identity and access management
  • policy management systems
  • cross-org initiatives

What the JD emphasized

  • 10 years building large‑scale system software
  • Deep expertise in secure system design
  • Strong command of security fundamentals
  • System‑level design and programming on UNIX/Linux
  • Solid understanding of major RDBMS internals and security features
  • Strong C/C++; or Java systems programming
  • Practical understanding of LLMs and GenAI system architectures
  • Experience securing agentic applications
  • Familiarity with the Model Context Protocol (MCP)
  • Knowledge of AI safety and compliance controls
  • Understanding of secure integration patterns between agents, identity platforms, and data planes
  • Awareness of emerging frameworks/standards for agent orchestration and secure plugin/tool ecosystems

Other signals

  • AI Database Security
  • AI agents
  • data security platform
  • secure agentic applications
  • LLMs and GenAI system architectures