The AI Security Institute is the world's largest and best-funded team dedicated to understanding advanced AI risks and translating that knowledge into action. We’re in the heart of the UK government with direct lines to No. 10 (the Prime Minister's office), and we work with frontier developers and governments globally.
We’re here because governments are critical for advanced AI going well, and UK AISI is uniquely positioned to mobilise them. With our resources, unique agility and international influence, this is the best place to shape both AI development and government action.
Interventions that secure a system from abuse by bad actors or misaligned AI systems will grow in importance as AI systems become more capable, autonomous, and integrated into society.
The Misuse Red Team is a specialised sub-team within AISI's wider Red Team. We red-team frontier AI safeguards for dangerous capabilities, research novel attack vectors, and develop advanced automated attack tooling. We share our findings with frontier AI companies (including Anthropic, OpenAI, DeepMind), key UK officials, and other governments to inform their respective deployment, research, and policy decision-making.
We have published on several topics, including novel automated attack algorithms (Boundary Point Jailbreaking), poisoning attacks, safeguards safety cases, defending finetuning APIs, third-party attacks on agents, agent misuse, and pre-training data filtering. Some example impact cases have been advancing the benchmarking of agent misuse, identifying novel vulnerabilities and collaborating with frontier labs to mitigate them, and producing insights into the feasibility and effectiveness of attacks and defences in data poisoning and fine-tuning APIs.
We’re looking for research scientists and research engineers for our misuse sub-team with expertise developing and analysing attacks and protections for systems based on large language models or who have broader experience with frontier LLM research and development. An ideal candidate would have a strong track record of performing and publishing novel and impactful research in these or other areas of LLM research. We’re looking for:
In practice, we can support staff’s work spanning or alternating between research and engineering. If you have a preference, please specify this in your application.
The team is currently led by Eric Winsor and Xander Davies – advised by Geoffrey Irving and Yarin Gal. You’ll work with incredible technical staff across AISI, including alumni from Anthropic, OpenAI, DeepMind, and top universities. You may also collaborate with external teams from Anthropic, OpenAI, and Gray Swan.
We are open to hires at junior, senior, staff and principal research scientist levels.
In accordance with the Civil Service Commission rules, the following list contains all selection criteria for the interview process.
The experiences listed below should be interpreted as examples of the expertise we're looking for, as opposed to a list of everything we expect to find in one applicant:
You may be a good fit if you have:
Strong candidates may also have:
Impact you couldn't have anywhere else
Resources & access
Growth & autonomy
Life & family*
*These benefits apply to direct employees. Benefits may differ for individuals joining through other employment arrangements such as secondments.
Annual salary is benchmarked to role scope and relevant experience. Most offers land between £65,000 and £145,000 made up of a base salary plus a technical allowance (take-home salary = base + technical allowance). An additional 28.97% employer pension contribution is paid on the base salary.
This role sits outside of the DDaT pay framework given the scope of this role requires in depth technical expertise in frontier AI safety, robustness and advanced AI architectures.
The full range of salaries are available below:
The interview process may vary candidate to candidate, however, you should expect a typical process to include some technical proficiency tests, discussions with a cross-section of our team at AISI (including non-technical staff), conversations with your team lead. The process will culminate in a conversation with members of the senior leadership team here at AISI.
Candidates should expect to go through some or all of the following stages once an application has been submitted:
Artificial Intelligence can be a useful tool to support your application, however, all examples and statements provided must be truthful, factually accurate and taken directly from your own experience. Where plagiarism has been identified (presenting the ideas and experiences of others, or generated by artificial intelligence, as your own) applications may be withdrawn and internal candidates may be subject to disciplinary action. Please see our candidate guidance for more information on appropriate and inappropriate use.
The Internal Fraud function of the Fraud, Error, Debt and Grants Function at the Cabinet Office processes details of civil servants who have been dismissed for committing internal fraud, or who would have been dismissed had they not resigned. The Cabinet Office receives the details from participating government organisations of civil servants who have been dismissed, or who would have been dismissed had they not resigned, for internal fraud. In instances such as this, civil servants are then banned for 5 years from further employment in the civil service. The Cabinet Office then processes this data and discloses a limited dataset back to DLUHC as a participating government organisations. DLUHC then carry out the pre employment checks so as to detect instances where known fraudsters are attempting to reapply for roles in the civil service. In this way, the policy is ensured and the repetition of internal fraud is prevented. For more information please see - Internal Fraud Register.
We may be able to offer roles to applicant from any nationality or background. As such we encourage you to apply even if you do not meet the standard nationality requirements (opens in a new window).