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About Us
Refractal is building security infrastructure for autonomy. Our founding team combines technical pedigree from MIT, NASA, Microsoft, and government with commercial experience in VC and startups. We have also been recognised by MIT's flagship CSAIL AI lab as part of CSAIL Alliances, as well as being selected for Google's highly selective Gemini Cybersecurity Startup Forum.
We are today working with regulated startups and a European government to secure their AI deployments. This role is an opportunity to join an ambitious, fast-paced startup at the very earliest stages.
The Mission
For most of the last decade, AI safety and security lived inside the frontier labs. They were the only ones thinking seriously about how those systems fail, get manipulated, or behave in ways they did not intend.
This is no longer the case. 2026 has become the year of AI Security; every company serious about deploying AI is now facing adversarial behaviour in production, with real data and consequences. At the same time, the risks have moved beyond the model(s) themselves: agents are being given credentials, tools, and decision-making authority faster than governance or security can catch up. Advanced prompt injection, goal hijacking, tool misuse, multi-agent collusion, and agentic data exfiltration — all of these are happening today.
The frontier labs are focused on securing their own models, and traditional cyber companies are not built for this problem. There is an opportunity to build a category-defining company for secure autonomy.
The Role: Founding AI Engineer
You will be one of the first engineering hires after the technical co-founder. You'll own parts of the platform from day one: agent classification, runtime evidence pipelines, and policy enforcement across models and modalities.
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You will have significant autonomy, direct customer impact, and a path to becoming Head of Engineering. You will be a natural technical leader who grows into owning the entire engineering organisation as we scale.
What you'll work on
- Developing the runtime classification stack that decides whether an agent's proposed action is authorised before it executes.
- Designing policy enforcement at the action boundary: allowing, blocking, or letting flagged actions proceed with sensitive data redacted.
- Building evidence pipelines that record every AI action, verdict, and rationale.
- Developing the policy engine that compiles natural-language policies and regulation into executable runtime controls.
- Building multimodal ingestion and detection.
- Collaborating with our security research function to turn novel attacks into shipped detections and controls.
- Owning systems end to end and shipping to production with real, high-consequence customer deployments.
What we're looking for
Someone hungry and technically brilliant. You care about getting AI safety and security right, but also believe that the market mechanism is perhaps the best way to do so.
You enjoy research, but only when grounded in real-world impact. You are a builder at heart, demonstrated through research at a top lab, production ML experience at a startup, or impressive open-source work. You think rigorously about how AI systems fail and how adversaries exploit them.
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Qualifications
- 0–3 years of post-university experience in AI/ML systems
- A strong technical foundation in computer science, machine learning, cybersecurity, or a related field.
- Evidence of exceptional building ability through production systems, research at a leading lab, startup experience, or open-source contributions.
- A rigorous understanding of how AI systems fail and how adversaries can exploit them.
- The ability to work independently, move quickly, and take ownership of complex technical problems.
- Strong communication skills and an interest in growing into a technical leadership role.
What we offer
- Competitive salary, founding equity, and a performance-linked bonus.
- Direct influence over the product, research agenda, and company direction.
- Access to real, high-consequence AI deployments rather than purely synthetic research environments.
- The chance to work directly with founders whose experience spans MIT, NASA, Microsoft, government, venture capital, and early-stage technology companies.
- London-based, with an in-person culture. We sponsor UK Skilled Worker and help Global Talent visas.
How to apply
Email careers@refractal-ai.com with your CV and a short note on the most interesting system you have broken, built, or studied. Links to research, write-ups, open-source work, are strongly encouraged.
Our process is fast: an intro call with the founders, a technical deep-dive on your past work, a short practical exercise, and an offer, typically within two weeks.
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