Lead AI Engineer

Lead AI Engineer – Fully Remote

£100,000 - £150,000 + Package

AI Connect are partnering with a major UK bank to help them hire a Lead AI Engineer to design, build, and deploy next-generation AI systems. You’ll join the leadership team of a growing AI function focused on delivering production-grade, application-level AI solutions that transform customer experience and internal workflows.

This is a hands-on leadership role where you’ll define technical direction, shape architecture, and build scalable agentic and multimodal systems that operate at enterprise scale.

What You’ll Do

• Design and deliver production-ready AI systems, focusing on real-world applications rather than experimental models.
• Build and integrate LLM-powered solutions using APIs from models such as OpenAI, Claude, and Gemini.
• Architect and implement agentic AI systems, including orchestration, tool usage, and multi-step reasoning workflows.
• Design and optimise RAG pipelines that leverage internal data to generate accurate, context-aware responses.
• Develop and implement evaluation frameworks to assess performance, reliability, and quality of AI systems.
• Work across multimodal use cases, including text, voice, and image-based interactions.
• Lead on solution design, system architecture, and technical strategy, ensuring systems are scalable, secure, and reliable.

Key Skills & Experience

• Proven experience as a Lead or Senior AI Engineer, building and deploying AI systems in production environments.
• Strong experience working with LLMs via APIs (e.g. OpenAI, Claude, Gemini) in real-world applications.
• Hands-on experience with agentic frameworks (e.g. LangGraph) and building multi-step AI workflows.
• Experience designing RAG architectures and working with enterprise data.
• Experience building evaluation frameworks for LLM or agent-based systems.
• Strong software engineering background (Python, APIs, microservices, distributed systems).
• Experience with cloud platforms (AWS, Azure, or GCP) and containerised environments (e.g. Kubernetes).
• Strong system design and architecture experience for scalable, high-performance applications.
• Experience working in regulated environments is advantageous but not essential.