Senior AI Software Engineer (GenAI)

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

What We're Looking For

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

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 LangChain and/or LangGraph

AKS, Kubernetes, Docker and Helm, * Azure AI Foundry

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

Not Suitable If

? Experience is primarily notebooks, research or experimentation

? No production LLM deployment experience

? No RAG implementation experience

? Limited software engineering or API development background