Chief AI Architect for Autonomous Cyber Agents

Chief AI Architect for Autonomous Cyber Agents

Full-Time 70000 - 90000 £ / year (est.) No working from home possible
Maze

At a Glance

  • Tasks: Lead AI research and implement strategies for cutting-edge vulnerability management.
  • Company: Maze, an innovative company focused on AI-native solutions.
  • Benefits: Competitive salary, flexible work environment, and opportunities for professional growth.
  • Other info: Join a small, dynamic team and shape the future of cybersecurity.
  • Why this job: Be at the forefront of AI technology and make a significant impact.
  • Qualifications: Strong background in AI and leadership experience in tech.

The predicted salary is between 70000 - 90000 £ per year.

Maze is building an AI-native vulnerability management platform.

As Head of AI, you will own the AI research and implementation strategy for the whole company, including the crown jewel technical problem behind it.

This is a hands-on leadership role with a small team of engineers, reporting to the CTO.

You will design evaluation frameworks for non‑deterministic agents, run fine-tuning and model routing experiments on real data, and prototype new techniques into the product.

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Chief AI Architect for Autonomous Cyber Agents employer: Maze

At Maze, we pride ourselves on being an exceptional employer that fosters a dynamic and innovative work culture. As a Full Stack Engineer, you'll enjoy significant autonomy in your role, working alongside a team of experts dedicated to building cutting-edge solutions at the intersection of generative AI and cybersecurity. With ample opportunities for professional growth and the chance to make a meaningful impact in a fast-paced startup environment, Maze is the perfect place for those looking to thrive and contribute to something extraordinary.

Maze

Contact Details:

Maze Recruitment Team

We think you need these skills to ace Chief AI Architect for Autonomous Cyber Agents

AI Research
Implementation Strategy
Hands-on Leadership
Team Management
Evaluation Frameworks Design
Non-deterministic Agents
Fine-tuning Experiments