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About the role
Senior AI Engineer – Generative & Agentic Systems
Bristol - Hybrid 2/3 days split
If you’ve built LLM systems that actually run in production, not just notebooks, this will interest you
You’ll be working on real-world AI in a regulated environment with security constraints, performance trade-offs etc
What you’ll actually get to build:
- Agentic systems using frameworks like LangChain, LangGraph or custom orchestration layers
- RAG pipelines using vector databases such as Pinecone, pgvector, Weaviate or similar
- Multimodal workflows combining text, image, voice or structured data
- Context engineering frameworks to optimise accuracy, latency and cost
- Python-based microservices built with clean architecture and strong OOP principles
- Cloud-native deployments across AWS, GCP or Azure using Docker, Kubernetes and CI/CD
- Evaluation pipelines, observability, logging and guardrails
What’s in it for you?
- Real ownership of architecture decisions
- Room to experiment and run POCs properly
- Production-grade constraints that make you sharper
- Cross-functional collaboration with Product and Design, not just “build what’s ticketed”
- A chance to define standards, not just follow them
This isn’t about chasing the newest model release
It’s about building AI systems that people trust
If you want to go deeper technically, ship properly engineered GenAI systems, and work somewhere where reliability actually matters, it’s worth a conversation
Apply directly or contact me
Cheryl@mbnsolutions.com
Cheryl
Dean
