Principal Software Security Engineer in Cambridge

The company's Vulnerability Research Tooling Team is looking for a Principal Software Engineer to help build AI-enabled tooling for hardware security issue identification. You will help design, build, and evolve systems that capture hardware security expertise and turn it into reusable datasets, analysis workflows, evaluation methods, and tooling. This role sits at the intersection of software engineering, AI tooling, data engineering, and security. The focus is to compose software and AI solutions that help detect security concerns across architectural specifications, RTL, firmware interfaces, software models, and hardware-software design assumptions.

We are seeking a Principal Software Engineer to play a meaningful role in establishing a new AI-enabled capability for hardware security issue identification. Working closely with hardware security experts, software security engineers, research collaborators, and platform teams, the role is responsible for turning expert review knowledge into scalable software systems. You will help define how hardware security expertise is captured, structured, evaluated, and applied through AI-assisted analysis workflows. This is not a traditional hardware validation or verification role. You do not need to be a hardware verification specialist. However, you should be comfortable building systems that help experts reason across architectural requirements, RTL, firmware connections, software representations, and hardware-software build assumptions.

As a Principal Engineer, you will be expected to create structure in an emerging area, influence technical direction, and help mature early prototypes into durable internal capabilities.

• Lead the design and delivery of AI-enabled tooling for hardware security issue identification across specifications, RTL, firmware interfaces, software models, and hardware-software boundaries.
• Develop analysis workflows and services that combine AI, retrieval, static analysis, automation, and human review to produce credible security findings.
• Partner across hardware engineering, software security, research, fuzzing, threat modelling, and platform teams to ensure the tooling is practical, technically grounded, and aligned with engineering workflows.
• Define evaluation approaches for AI-assisted security analysis, including benchmark tasks, ground truth, confidence measures, false-positive handling, and evidence quality.
• Contribute to the long-term roadmap for hardware security AI tooling, including prototype evolution, productionisation, platform integration, and future research directions.

• Significant experience designing and building software systems using modern backend, data, platform, or developer tooling engineering practices.
• Experience building AI-enabled tooling, data-heavy engineering systems, analysis platforms, developer tools, or automation for complex technical domains.
• Practical understanding of LLM-based systems, including retrieval, embeddings, context engineering, structured outputs, tool/function calling, workflow orchestration, and AI-assisted analysis patterns.
• Familiarity with sophisticated AI workflow techniques such as agentic workflows, task decomposition, evaluator/critic loops, human-in-the-loop review, context or memory systems, and traceable evidence generation.
• Ability to work with domain experts, extract tacit knowledge, and translate it into structured data, software workflows, evaluation criteria, and maintainable tooling.
• Ability to influence technical direction and collaborate effectively across security, software, hardware, research, and platform teams.

• Exposure to hardware architecture, RTL, firmware, SoC design, CPU/GPU systems, or hardware/software interfaces.
• Exposure to hardware security, platform security, vulnerability research, secure development, or threat modelling.
• Experience with static analysis, symbolic analysis, formal methods, or other automated techniques.
• Experience building datasets, benchmarks, evaluation harnesses, or test corpora for AI-assisted analysis.
• Familiarity with cloud, containerised development, infrastructure-as-code, CI/CD, observability, or internal engineering platforms.
• Experience collaborating with research teams or translating research ideas into production engineering workflows.

The company is an equal opportunity employer, committed to providing an environment of mutual respect where equal opportunities are available to all applicants and colleagues. We are a diverse organization of dedicated and innovative individuals, and don’t discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Salary Range £126,200 – £170,800 per year.