2026 Phd Software Engineering Internship, Security, Amsterdam

Uber Uber · Consumer · Amsterdam, Netherlands · University

PhD internship focused on AI-first security, researching and implementing AI agents to interact with security platforms, building models for identity risk assessment, and developing LLM-driven layers for vulnerability prioritization within Uber's production ecosystem.

What you'd actually do

  1. Research and implement AI agents to interact with our security platforms, providing the next level of intelligence for safe decision-making.
  2. Navigate the messiness of credential usage data to build models that distinguish between active and obsolete identities and risk they present.
  3. Help design a strategy to track AI agents and automated identities to ensure we can distinguish between legitimate agentic access and a security breach.
  4. Advance our security posture by building an LLM-driven layer on top of our security data to prioritize the most critical vulnerabilities.
  5. Move from ideation to a prototype that works within Uber’s production ecosystem, proving that our knowledge base is sound and trustworthy.

Skills

Required

  • Currently enrolled in a PhD program in Computer Science, Cybersecurity, Machine Learning, or a related technical field.
  • Experience with (or a strong inclination to learn) AI-driven development.
  • Ability to commit to 3 months of full-time work in our Amsterdam office starting in June 2026.

Nice to have

  • Experience with platform security like PKI systems, secrets management, or identity frameworks.
  • Exposure to infrastructure-as-code and automation tools (Terraform, Ansible, etc.).
  • Understanding of secure communication protocols (e.g., TLS, mTLS, OAuth).
  • Familiarity with DevOps tooling and CI/CD pipelines.
  • Ability to translate complex security risks into elegant, scalable technical solutions for both technical and business partners.

What the JD emphasized

  • AI-First Security
  • AI agents
  • LLM-driven layer

Other signals

  • AI agents for security platforms
  • Models to distinguish active vs obsolete identities
  • Track AI agents and automated identities
  • LLM-driven layer for vulnerability prioritization