Alignment Red Team - Research Engineer/Research Scientist

About the AI Security Institute

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.

The deadline for applying to this role is 11th October 2026, end of day, anywhere on Earth.  

Team Description   

Risks from misaligned AI systems are growing increasingly important as AI systems become more capable, autonomous, and integrated into society. Understanding these risks and stress-testing mitigations is crucial to ensuring advanced AI systems are developed and deployed safely and beneficially in the future. 
 
The Alignment Red Team is a specialised subteam within AISI's wider Red Team focused on detecting and evaluating misalignment in frontier AI systems. We perform novel research to develop techniques for finding misalignment, and pre- and post-deployment evaluations of frontier AI systems to understand loss-of-control risks associated with models, such as deceptive alignment, research sabotage, and reward-seeking. We share our findings with frontier AI companies and the UK and allied governments, to inform their respective deployments, research, and policy-making. We also work directly with safety teams at frontier labs, sharing our evaluation findings to help improve their model alignment training and monitoring methodology. 

We have conducted pre-deployment testing with multiple frontier AI companies for propensities related to research sabotage, cheating and unsanctioned cyber-attacks. We previously found that Claude models would sometimes refuse to help with benign AI safety research, an issue which Anthropic then evaluated for and fixed in their next model release. 

About the Role 

We're seeking Research Engineers and Research Scientists to join our Alignment Red Team. We are open to hires at junior, senior, staff and principal research scientist/engineer levels. 

What You'll Be Doing 

• Researching methods to automatically search for misalignment in frontier models, including misalignment related to loss-of-control risks such as research sabotage and reward-seeking. 
• Building and running alignment evaluations relevant for loss-of-control risks that current benchmarks don’t capture. 
• Running pre-deployment evaluations to test the alignment of AI systems, and analysing and reporting results to frontier AI companies and UK and allied governments. 
• Contributing to public-facing research publications (like our published alignment evaluation case study) and technical reports that advance the field's understanding of misalignment risks and alignment evaluation methodology. 
• Designing and building software and tooling, including open-source software, for better alignment evaluations, improving efficiency, realism, and usability. 

The work could also involve

• Conducting threat modelling, analysis, and conceptual thinking to understand crucial model behaviours that could lead to loss of control (e.g. AI research assistants at frontier labs), translating abstract risk concepts into concrete, testable hypotheses.
• Performing alignment incident investigations to understand after the fact what drove certain kinds of misaligned behaviour in frontier models. 
  
• Mentoring and advising external collaborators and researchers to do work relevant to the team’s goals and alignment testing more broadly. 

Who we're looking for

Essential requirements

• Ability to work autonomously on complex research projects involving substantial engineering. Have completed at least one significant research project in AI safety, security or alignment involving engineering, experiment design and analysis on frontier LLMs. 
  
• Strong software engineering and ML experience writing complex projects involving language models and ML, beyond just research code. 1+ years professional experience programming in Python for ML or SWE work. 
• Experience writing clean, documented research code for machine learning experiments, including experience with ML frameworks like PyTorch or evaluation frameworks like Inspect. 
• Proven ability in a team environment – flexible, adaptive to needs, and willing to contribute wherever necessary. 
• Impact-driven mindset, motivated by doing the most important work rather than what's superficially impressive. 
• High velocity and high-quality bar for outputs. 

Highly Desirable

We don't expect candidates to have all of these – they're additional signals that help us identify exceptional fits for specific aspects of the role. 

• Ability to make high-quality decisions by identifying risks and testing assumptions, demonstrated through strong prioritisation of research projects using clear, systematic criteria such as potential impact, feasibility, and the relative novelty of the research area.
• Familiarity with alignment literature, current methods for post-training and aligning LLMs, loss-of-control risks and threat models, and the current state of the field. 
• High-quality research papers (first author at top ML venues such as NeurIPS, ICLR or ICML), particularly in relevant areas (such as AI safety, alignment, control, adversarial ML or evaluations). 
• Professional experience working on alignment or evaluations, especially at frontier labs or other frontier 3rd party evaluators. 
• Strong open-source software projects, particularly related to LLMs.
• Proficient usage of LLM coding tools and agents. 

Selection process

The interview process may vary from 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) and 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:   

• Initial assessment
• Initial screening call
• Technical assessment 
• Research interview
• Behavioural interview
• Final interview with members of the senior leadership team

What We Offer 

Impact you couldn't have anywhere else 

• Incredibly talented, mission-driven and supportive colleagues. 

• Direct influence on how frontier AI is governed and deployed globally. 

• Work with the Prime Minister’s AI Advisor and leading AI companies. 

• Opportunity to shape the first & best-resourced public-interest research team focused on AI security. 

Resources & access 

• Pre-release access to multiple frontier models and ample compute. 

• Extensive operational support so you can focus on research and ship quickly. 

• Work with experts across national security, policy, AI research and adjacent sciences. 

Growth & autonomy 

• If you’re talented and driven, you’ll own important problems early. 

• 5 days off and annual stipends for learning and development, and funding for conferences and external collaborations. 

• Freedom to pursue research bets without product pressure. 

• Opportunities to publish and collaborate externally. 

Life & family* 

• Modern central London office, or where applicable, option to work in similar government offices in Birmingham, Cardiff, Darlington, Edinburgh, Salford or Bristol. 

• Hybrid working, flexibility for occasional remote work abroad and stipends for work-from-home equipment. 

• At least 25 days’ annual leave, 8 public holidays, extra team-wide breaks and 3 days off for volunteering. 

• Generous paid parental leave (36 weeks of UK statutory leave shared between parents + 3 extra paid weeks + option for additional unpaid time). 

• On top of your salary, we contribute 28.97% of your base salary to your pension. 

• Discounts and benefits for cycling to work, donations and retail/gyms. 
   

*These benefits apply to direct employees. Benefits may differ for individuals joining through other employment arrangements such as secondments. 

Salary

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: 

• Level 3: £65,000–£75,000 (Base £39,850 + Technical Allowance £25,150–£35,150)
• Level 4: £85,000–£95,000 (Base £47,355 + Technical Allowance £37,645–£47,645)
• Level 5: £105,000–£115,000 (Base £61,620 + Technical Allowance £43,380–£53,380)
• Level 6: £125,000–£135,000 (Base £74,605 + Technical Allowance £50,395–£60,395)
• Level 7: £145,000 (Base £74,605 + Technical Allowance £70,395)

Additional Information

Use of AI in Applications

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.

Internal Fraud Database 

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.

Security

Nationality requirements

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).

Working for the Civil Service

Diversity and Inclusion

Find more English Speaking Jobs in United Kingdom on Arbeitnow