Engineering Lead - Human Influence

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 Human Influence (HI) team focuses on the ways in which AI can influence human beliefs, decisions, and behaviour. A substantial class of AI risk operates through people. AI systems can persuade people to change their beliefs and to take action; can build trusting relationships with people in order to exploit them; can extract private information from them; and can hold delegated ownership of high-stakes decisions. Our work is highly interdisciplinary, drawing on methods from computational social science, AI safety and security, cognitive and behavioural science, machine learning, and data science. Typical projects include running rigorous human-AI interaction studies and randomised controlled trials, building evaluations and benchmarks that track AI capabilities across model releases, eliciting model capabilities through fine-tuning and self-play, and developing datasets to monitor real-world risk exposure and severity.

We are looking for an Engineering Lead to manage and oversee a growing team of engineers. The team’s work includes: developing new evaluations and technical capability demonstrations, building robust data pipelines, driving world-leading research studies using complex multi-agent setups, finetuning LLMs (>100B parameters), and building custom Reinforcement Learning environments.

Projects the Engineering Lead might lead or deliver as individual contributor include:

• Designing the scalable system architecture underpinning the repeatable delivery and analysis of model evaluations and benchmarks.
• Building an automated pipeline that recruits participants and runs a human-AI experiment end-to-end, to track how a given capability shifts with each new model release.
• Designing and building a toolkit for multi-agent studies, which allows researchers to run synthetic as well as human-in-the-loop studies seamlessly and with performance guarantees.
• Delivering ambitious, engineering-heavy research projects on Human Influence topics, for instance by leveraging post-training techniques on a large compute cluster.

This is a leadership role. Competitive candidates will be strong engineers with a track record of leading engineering projects from scoping to production. The Human Influence Engineering Lead will work with Human Influence team leadership and senior AISI stakeholders to develop and deliver an engineering roadmap for the Human Influence team, and will lead and grow the HI Engineering function, including managing Research and Software Engineers.

This is a multidisciplinary team, and successful candidates come from a wide range of backgrounds.

General:

• Experience leading a complex engineering or research project from scoping to deployment or publication.
• Clear understanding and views on how AI and coding assistants should change how an engineering team works and interacts with research teams.
• Clear understanding of the current AI safety literature, and an interest in topics relevant to Human Influence.
• Clear and consistent communication.

Research and engineering:

• Experience translating research questions into reproducible engineering tasks.
• Proven experience working with non-technical stakeholders to support a product or research roadmap, e.g., leading to a product with actual users, benchmarks and evaluations, or a research paper.
• Clear grasp of software design concepts, especially for cloud deployments and databases, e.g. using Docker, Kubernetes, or AWS primitives – production experience preferred.
• Writing scalable and maintainable production code in (at least) Python.
• Experience building or finetuning an ML model, ideally an LLM, using common libraries like PyTorch, Keras, JAX, or custom code.
• Experience shipping an AI safety pipeline to production (e.g. evaluations, monitoring, serving custom models), going beyond research prototypes.
• Experience using data to answer complex research questions, e.g. by scoping, training, and validating a classifier or finetuned LLM.
• Experience with frontend (e.g. TypeScript) and node.js deployments.
• Line management experience of at least 1 year.
• Experience hiring and mentoring technical staff.

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.
• 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.
• 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. 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.