Application Guide

How to Apply for Senior Security Engineer, Agentic Red Team

at Google DeepMind

🏢 About Google DeepMind

Google DeepMind is a world leader in artificial intelligence research, known for groundbreaking achievements like AlphaGo and AlphaFold. Working here means collaborating with top AI researchers on cutting-edge problems that shape the future of technology, with a culture that values ambitious, long-term thinking and real-world impact.

About This Role

This Senior Security Engineer role focuses on offensive security testing of agentic AI systems, specifically targeting vulnerabilities unique to generative AI and autonomous agents. You'll conduct rapid red team assessments, build automated exploit frameworks, and embed with product teams to secure next-generation AI services before deployment.

💡 A Day in the Life

You might start by reviewing new agentic service designs with product teams, identifying potential attack vectors during architecture discussions. Later, you'd conduct rapid security assessments on staging environments, developing exploits for prompt injection vulnerabilities, then code automation to detect similar issues in future model versions. The day often ends with documenting findings and collaborating with defensive engineers to implement mitigations.

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Interview Prep

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🎯 Who Google DeepMind Is Looking For

  • Has hands-on experience in red teaming or adversarial ML, with proven ability to find and exploit novel vulnerabilities in complex systems
  • Demonstrates strong Python/Go/C++ coding skills through security tool development or automation projects, particularly related to AI/ML systems
  • Possesses deep technical understanding of LLM architectures, agentic workflows (like chain-of-thought reasoning), and AI-specific attack vectors
  • Can bridge offensive security findings into defensive engineering solutions, showing experience in building automated testing frameworks

📝 Tips for Applying to Google DeepMind

1

Highlight specific examples of red teaming or adversarial ML projects where you exploited non-deterministic behaviors or novel AI vulnerabilities

2

Showcase security tools you've built in Python/Go/C++ that automate attack sequences or vulnerability discovery, ideally related to AI systems

3

Demonstrate understanding of Google DeepMind's research publications on AI safety and how your skills align with their technical direction

4

Include metrics on how your red team findings were transformed into automated defenses or prevented regression in production systems

5

Emphasize experience working directly with product teams during design phases, not just post-deployment testing

✉️ What to Emphasize in Your Cover Letter

['Specific examples of discovering and exploiting AI-specific vulnerabilities like prompt injection or tool-use escalation in real systems', "Experience building 'Auto Red Teaming' frameworks or similar automation that turns manual findings into regression prevention", 'Ability to communicate complex security risks to non-security audiences and influence product design decisions', "Understanding of Google DeepMind's approach to AI safety and how your skills advance their mission of developing beneficial AI"]

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Google DeepMind's publications on AI safety, particularly those related to red teaming or adversarial testing of AI systems
  • → The specific agentic services and products Google DeepMind has announced or is developing (beyond just research papers)
  • → Google's broader AI security initiatives and how this role might interface with other security teams across Alphabet
  • → Recent talks or blog posts from DeepMind security researchers about their approach to securing autonomous AI systems

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Walk through a specific red team engagement where you exploited agentic AI vulnerabilities, focusing on your methodology and impact
2 Technical deep dive on implementing automated defenses against prompt injection or tool-use escalation attacks
3 Coding challenge involving building a security tool in Python/Go to automate detection of AI logic errors or data poisoning vectors
4 Scenario-based question on how you'd conduct a rapid security assessment of a new agentic service during design phase
5 Discussion of recent AI security research papers and how you'd apply those concepts to Google DeepMind's agentic systems
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⚠️ Common Mistakes to Avoid

  • Focusing only on traditional application security without demonstrating specific knowledge of AI/ML attack vectors and defenses
  • Presenting generic red teaming experience without examples of rapid, agile assessments or embedding with product teams
  • Listing AI/ML knowledge superficially without being able to discuss technical details of LLM architectures or agentic workflows

📅 Application Timeline

This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.

Typical hiring timeline:

1

Application Review

1-2 weeks

2

Initial Screening

Phone call or written assessment

3

Interviews

1-2 rounds, usually virtual

✓

Offer

Congratulations!

Ready to Apply?

Good luck with your application to Google DeepMind!

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