Workstream Lead, Agentic AI Risk Modelling

The deadline for applying to this role is Tuesday 13th October 2026, end of day, anywhere on Earth. 

Job summary 

Within AISI’s Research Unit, the Agentic AI Risk Modelling team studies how advanced AI systems could become difficult to oversee, correct or shut down as they take on longer and more autonomous tasks. The team builds scenario-based risk models that extend published work on AI timelines and systemic risk and uses them to identify practical mitigations such as monitoring infrastructure, deployment guidance and containment protocols. Its analysis has been shared across government and is intended to inform real decisions by the organisations best placed to act. 

We are looking for a Workstream Lead to lead and line-manage this team through its next phase. You will shape the team’s strategy and research agenda, set the scientific direction of its work, and ensure that promising mitigations move from analysis into adoption. This is a senior leadership role for someone who can combine technical judgement, strategic thinking, delivery focus and strong people leadership in a fast-moving and highly consequential area. 

This role sits within AISI’s Research Unit and reports to a Research Unit Deputy Director. 

Job description 

As Workstream Lead for Agentic AI Risk Modelling, you will provide the scientific, strategic and managerial leadership needed to keep the team at the forefront of this area. 

You will be accountable for the team’s research agenda and for the routes to implementation of any mitigations it identifies. This includes setting priorities, choosing analytical approaches, reviewing the quality of outputs, and ensuring the work is relevant to the institutions that can act on it. You will also lead and develop a multidisciplinary team, oversee multiple strands of work at once, and build strong relationships with senior policy and technical stakeholders across government, research organisations and frontier AI companies. 

The team’s aim for March 2027 is for the UK organisations best placed to act to have adopted its existing mitigations, and for newly identified mitigations to move more quickly from research to adoption. You will play a central role in achieving that aim. 

Role summary 

You will: 

• Set the team’s strategy, quarterly plan and overall research agenda; 

• Lead the scientific direction of the team’s risk modelling, including selecting approaches, choosing which scenarios to develop, and reviewing outputs; 

• Develop analyses of how advanced AI systems could become difficult to oversee, correct or shut down, and identify practical ways to reduce those risks; 

• Turn research into assessments, mitigations and implementation pathways, and work with relevant UK organisations to support adoption; 

• Hire, line-manage and develop a multidisciplinary team, maintaining high standards across multiple strands of work; 

• Build trusted relationships with senior policy and technical staff across government, as well as leaders in research organisations and frontier AI companies; 

• Work with other AISI research leaders on priorities, quality and delivery across the Research Unit. 

Person specification 

In accordance with the Civil Service Commission rules, the following list contains all selection criteria for the interview process. 

Essential criteria 

• Experience of leading impactful research, scientific work, or technical programmes relevant to frontier AI, AI safety, AI governance, risk analysis, or a closely related field; 

• Strong strategic judgement on advanced AI risks and the ability to identify the most important questions in a fast-moving and uncertain area; 

• Experience of setting and delivering research agendas or analytical programmes in technically complex environments; 

• Ability to lead high-quality analytical or scientific work, including setting direction, reviewing outputs critically, and maintaining rigorous standards; 

• Experience of translating technical or research findings into practical recommendations, operational interventions, or policy-relevant outputs; 

• Track record of successfully leading and line-managing high-performing multidisciplinary teams, including developing more junior staff; 

• Experience of building effective relationships with senior stakeholders, including in government, academia, industry, or other complex institutional environments; 

• Strong written and verbal communication skills, with the ability to communicate complex issues clearly to both technical and non-technical audiences. 

Desirable criteria 

• Expertise in one or more areas relevant to the team’s remit, such as AI control, alignment, model autonomy, scenario analysis, systemic risk, or frontier AI governance; 

• Understanding of published work on frontier AI timelines, advanced AI risk, or loss of control; 

• Experience designing or evaluating mitigations for high-consequence technical risks; 

• Background in machine learning, computer science, engineering, mathematics, economics, public policy, security studies, or another relevant discipline; 

• Familiarity with government decision-making, national security, or assurance processes.