Lead AI Engineer

Lead AI Engineer – Generative & Agentic Systems

Bristol - Hybrid 2/3 days split

If you’ve architected LLM systems that run in production, not just built features inside them, this will interest you

You’ll be leading the design and delivery of real-world AI in a regulated environment with security constraints, performance trade-offs and scalability decisions that actually matter.

What you’ll actually be responsible for:

• Architecting agentic systems using LangChain, LangGraph or custom orchestration layers
• Designing scalable RAG pipelines using vector databases such as Pinecone, pgvector, Weaviate or similar
• Defining multimodal workflows combining text, image, voice or structured data
• Setting context engineering standards to optimise accuracy, latency and cost
• Leading Python-based microservice architecture built on clean, scalable principles
• Owning cloud-native deployments across AWS, GCP or Azure using Docker, Kubernetes and CI/CD
• Establishing evaluation frameworks, observability standards, logging and guardrails

What’s in it for you?

True architectural ownership
Influence over technical direction and engineering standards
Room to run POCs properly and explore emerging techniques
Close collaboration with Product and Design at decision level
The chance to build AI systems that are trusted in production

This isn’t about prompting tricks
It’s about systems thinking, technical depth and setting the bar for how AI is built

If you want to shape how agentic and generative systems are architected, not just contribute to them, it’s worth a conversation

Apply directly or contact me

Cheryl@mbnsolutions.com