Senior AI Software Engineer (GenAI)

We're looking for a hands on Generative AI Engineer to build, deploy and secure production grade AI applications within a regulated enterprise environment.

This is not a research or proof of concept role. We're looking for someone who has delivered real world GenAI solutions and can clearly explain both the concepts and the implementation behind them.

Building and deploying production LLM applications

Strong experience with RAG including:

• Document ingestion
• Chunking strategies
• Embeddings
• Vector search and retrieval
• Context engineering
• Prompt orchestration

LLM deployment experience, not just experimentation

Azure OpenAI, Ollama and/or Vertex AI

Python, FastAPI and REST API development

AKS, Kubernetes, Docker and Helm

Secure AI development and DevSecOps practices including:

• RBAC
• Azure AD
• Key Vault
• Secrets management
• Secure deployment patterns
• Auditability and governance

LLM evaluation and optimisation including:

• Grounding
• Hallucination detection
• Response quality measurement
• Accuracy testing
• Prompt and context engineering

You should be able to confidently explain:

• What RAG is and how to build it end to end
• How embeddings and vector databases work
• How to deploy and operate LLMs in production
• How to secure AI systems and protect sensitive data
• How to evaluate and improve model performance
• How to expose AI capabilities through APIs and enterprise applications

• Azure AI Foundry
• Agentic AI
• MCP
• Private LLM deployments
• Enterprise security and regulated environments

❌ Experience is primarily notebooks, research or experimentation

❌ No production LLM deployment experience

❌ No RAG implementation experience

❌ Limited software engineering or API development background

If you've built, deployed, secured and evaluated GenAI solutions in production and can explain the architecture and decisions behind then either;

Call Claire Thomas, add on Linkedin or apply to this advert & I will come back