Senior Software Engineer, Chem-Bio

Aisi; Greater London; On-site; GBP 70,000 - 120,000; Full time

Job summary

AI Security Institute in the United Kingdom is seeking a senior individual contributor to build and maintain the CB team's engineering platforms. You will design core platform components that enable researchers to run experiments and ship results quickly, including LLM-based agent systems, evaluation frameworks, and supporting infrastructure.

You will collaborate with researchers across AI risk and CB domains, own and deliver major engineering projects, write robust production Python, ensure

Qualifications

• Production-grade Python experience with scalable systems.
• Strong infra skills: AWS, Kubernetes, and job scheduling.
• Ability to translate varied research needs into engineering plans.
• Experience owning technical projects as a senior contributor.

Responsibilities

• Design and build core platform components enabling researchers to run experiments.
• Work closely with researchers to translate CB research needs into engineered systems.
• Own significant engineering work from design through implementation and maintenance.
• Write high-quality production code with testing, documentation, and observability.
• Contribute to engineering standards and practices within the team.
• Collaborate across teams to share tooling and avoid duplication.
• Mentor others through technical leadership without formal line management.

Skills

Python

AWS

Kubernetes

OpenAI APIs

Research collaboration

Communication

Tools

Slurm

PyTorch

Job description

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.

About the Team

AISI's Chem Bio (CB) team conducts technical research to assess evolving AI capabilities related to science R&D and CB misuse, and the effectiveness of technical safeguards that might mitigate risks arising from those capabilities.

The goal of our research is to inform critical decisions on security, opportunities, policy, and risk mitigation made by governments and AI developers.

We're a close-knit, unusually interdisciplinary team-made up of machine learning researchers and engineers, software engineers, virologists and bacteriologists, behavioural research scientists, biosecurity experts, long-standing CB policy specialists and talented generalists-who work closely with other technical and policy teams across government.

Role Responsibilities

We are building a dedicated engineering function within the CB team - a small team that owns the shared platform, tooling, and infrastructure that our research projects depend on. This role is a senior individual contributor within that function. The successful candidate will:

• Design and build reliable systems - architect and deliver core platform components that enable researchers to run experiments and ship results quickly, including LLM-based agent systems, evaluation frameworks, and supporting infrastructure.
• Work closely with researchers - translate varied research needs across general agents, science agents, chemical and biological models and other CB workstreams into well-engineered, maintainable systems.
• Own and deliver significant engineering work - take responsibility for substantial technical projects and shared components, driving them from design through implementation, iteration, and maintenance.
• Write high-quality production code - build scalable, robust, and maintainable software, primarily in Python, with strong engineering discipline around testing, documentation, and observability.
• Contribute to engineering standards and practices - help improve code quality, development workflows, and shared engineering approaches within a growing engineering team embedded in a research-heavy environment.
• Collaborate across AISI - work with our Core Technology and engineering teams to share tooling, align on infrastructure, and avoid duplication.
• Support technical direction - contribute to architectural decisions, identify opportunities to strengthen shared infrastructure, and help make pragmatic technical trade-offs.
• Mentor others through technical leadership - support other engineers through collaboration, code review, and knowledge sharing, without formal line-management responsibility.

Role Requirements

We are looking for the following skills, experience and attitudes, but a successful candidate will not necessarily need to meet all these criteria. We can be flexible in shaping the role and salary to your background, expertise, and level of experience.

• Significant experience writing production-level Python code that is scalable, robust, and easy to maintain, with a track record of delivering substantial technical work.
• Strong infrastructure and platform skills - experience with cloud environments (AWS), container orchestration (Kubernetes), and job scheduling (Slurm or similar).
• Experience owning technical projects or major systems as a senior individual contributor. You do not need formal management experience for this role.
• Familiarity with the AI/ML ecosystem: OpenAI-compatible APIs, PyTorch, and the tooling around LLM-based systems.
• Ability to work across multiple teams, understanding varied research needs and delivering reliable engineering solutions.
• A sense of mission, urgency, and responsibility for success: Demonstrated ability to solve challenging problems, implement solutions efficiently and acquire any missing knowledge necessary to get the job done. Motivated to build software with direct policy impact.
• Strong communication skills, with the ability to work effectively in a dynamic, multidisciplinary team environment.

Strong candidates may also have:

• Experience working in a research environment - you don't need to be a researcher, but you should be comfortable working alongside them and translating ambiguous research requirements into engineering plans.
• Familiarity with computational biology tools, workflows, or datasets.
• Experience building or main