Senior AI Engineer

What you’ll be doing You’ll work across the full AI lifecycle from experimentation and data engineering through to deployment, monitoring and optimisation. - Build and deploy production-grade AI applications using LLMs, RAG and modern AI architectures - Develop agentic workflows, vector search, embeddings and semantic search - Build scalable data pipelines using Databricks, Python, PySpark and SQL - Develop evaluation and benchmarking frameworks to measure AI performance - Take AI solutions from POC → production - Implement monitoring, observability and quality controls - Establish best practices across MLOps, CI/CD, model versioning and reproducibility - Work directly with product, engineering and business stakeholders - Influence architecture and the wider AI roadmap - Mentor engineers and help raise technical standards across the team What they’re looking for Essential: - Strong commercial experience as a Senior AI Engineer, ML Engineer or AI-focused Data Engineer - Expert-level Python - Strong data engineering + SQL skills - Production experience with Databricks - Hands-on experience building LLM-powered applications - Strong understanding of RAG, vector databases, embeddings and semantic search - Experience taking AI systems into production and improving them post-deployment - Experience with Azure, ideally Azure OpenAI and related AI services - Strong software engineering fundamentals — testing, Git, CI/CD and scalable system design - Experience leading projects and working directly with senior stakeholders Why this role? This isn't a role where you'll spend 12 months building another AI demo that nobody uses. The foundations are already there data, infrastructure, investment and executive backing. You'll have the opportunity to take ownership of genuinely important AI products, influence architecture and help shape how AI is embedded across an entire professional services business.