Lead AI Engineer

You will join a growing technology business at a pivotal stage in its AI journey. These are the first dedicated AI engineering hires in the team, so you will have the chance to shape how AI is designed, built, and deployed across a live cybersecurity product environment.

Initially, your focus will sit within the cyber division, where you will work on AI-driven initiatives tied to vulnerability management, penetration testing workflows, remediation checking, intelligent reporting, and automation. Longer term, there is scope for the role to expand into wider product areas across the group.

This is a hands-on engineering role with real ownership. You will take AI projects from concept through to production, not just build prototypes and hand them over. You will be expected to design, develop, deploy, monitor, and maintain scalable AI services that integrate into existing platforms via APIs and microservices.

What They’re Looking For:

• The key requirement is strong, real-world AI engineering capability. They need someone who can build and deliver, not someone who has only experimented on the edges of AI.
• You will ideally bring:

• AI/ML engineering experience in production environments
• LLM development and orchestration experience
• Python development
• Cloud platform experience across AWS or Azure or GCP
• End-to-end delivery experience from idea and prototyping through to deployment and support
• Experience building scalable services and APIs
• Strong communication skills and the ability to work closely with developers and stakeholders
• A self-starting approach with the confidence to own your workload and move initiatives forward
• Cybersecurity knowledge is not essential. That can be taught. The non-negotiable is deep AI and machine learning expertise.

What You’ll Work With:

You will work across a modern AI and product environment, with plenty of room to influence standards and tooling as the function matures. Likely technologies and themes include:

• Python development
• OpenAI models
• Anthropic models
• AWS Bedrock
• LLM workflows
• Agentic AI systems
• Machine learning algorithms
• API-led microservices
• Cloud platforms
• Monitoring, management, and alerting
• Vulnerability management workflows
• AI-assisted report generation
• Security testing automation

The current product direction is centred on building AI capabilities as services outside the main platform, then integrating them back in via APIs. That means the work has a genuine R&D feel, but always with a clear path into production.

Nice to Haves:

• Cybersecurity experience
• Penetration testing exposure
• Vulnerability management knowledge
• Agent-based system design
• Content analysis or anomaly detection experience
• MLOps understanding
• Enterprise environment experience
• Change control awareness
• KPI or ROI tracking experience
• Leadership or mentoring capability
• Product or solutions thinking

Why Join / Projects:

You will be joining very early in the AI build-out, which means high ownership, a broad remit, and the chance to make a visible impact. Early projects are expected to include:

• AI-powered remediation checking following penetration tests
• Worker or agent-style services that perform specific testing tasks and report findings back
• LLM-powered reporting and consultant support tools
• AI modules for external, web, cloud, and later internal testing use cases
• Statistical analysis and machine learning models for wider business applications over time
• Reusable AI services that can eventually support multiple products and business units

This role will suit someone who enjoys solving complex problems, working in ambiguity, and building things properly from the ground up. There is likely to be a blend of seniority across the hires, so candidates with leadership potential or experience guiding others will be particularly valuable.

You will report initially into the cyber product and technology function, with close collaboration across product, architecture, engineering, and technical leadership.