AI Engineer

Are you an AI native Software Engineer who is already using AI agents to build software and wants to help organisations make the leap to truly agentic development?

You could be progressing your career in a senior, hands-on AI Engineer role at a massively profitable Private Equity firm that invests in businesses across the finance, investment management and insurance space.

As an AI Engineer you’ll join a small, highly capable technology team working with enterprise clients to build AI first software factories and prepare businesses for agentic transformation. You’ll work across multiple projects, helping establish the foundations for AI driven development, from integrations and data pipelines through to agent development, DevOps and CI/CD.

The role could suit two closely related profiles: an Agentic Systems Engineer experienced in building and deploying AI agents at enterprise scale, with a strong understanding of architecture, security, compliance and observability; or an AI Software Factory Lead who can establish the frameworks, integrations, tooling and engineering practices needed to enable software development with AI at scale. The ideal candidate can span both.

• You have hands-on experience coding with AI agents across multiple programming languages
• You have strong backend development experience (likely Python or other OO language), DevOps and CI/CD experience are important, alongside AWS and / or Azure
• You have a good knowledge of solution architecture, technical design, reviewing AI generated builds and translating business requirements into robust software solutions
• You have a strong knowledge of security, compliance and observability
• You’re collaborative and pragmatic with excellent communication and stakeholder management skills, you’re able to influence others and drive change
• Experience with MCP and building servers is desirable

• Competitive salary, to £110k + bonus
• Hybrid working
• 30 days Holiday
• Wellness budget
• Life and Health insurance
• Pension
• Enhanced Maternity and Paternity leave
• Cycle to work scheme
• Training budget
• Flexible working patterns