Senior AI Consultant

Role Overview

• Help customers implement a large language model, geared to solving complex and advanced business challenges.
• Deploy an end-to-end ML pipeline to streamline and automate the AI offerings of some of the largest organisations in the world.

Requirements

• PhD in a relevant field, such as Machine Learning, Computer Science, Artificial Intelligence, Data Science, Mathematics, or a closely related discipline.
• Proven experience designing and deploying GenAI and agentic AI solutions using tools such as Databricks Mosaic AI Agent Framework, Azure AI Studio, and Azure OpenAI Service.
• Expertise in building production‑grade RAG pipelines, including chunking strategies, vector search, retrieval evaluation, and end‑to‑end optimisation.
• Hands‑on experience with Large Language Models (LLMs) in enterprise environments, including prompt engineering, fine‑tuning, guardrail implementation, and responsible AI practices.
• Ability to develop and deploy AI agents with tool use, memory, and multi‑step reasoning using frameworks like LangChain, LangGraph, Semantic Kernel, or CrewAI.
• Strong LLMOps and MLOps skills, including model evaluation, A/B testing, monitoring, and CI/CD for AI workflows (e.g., Databricks Asset Bundles, GitHub Actions, Azure DevOps).
• Proficiency in writing production‑quality Python, with the ability to support AI projects from initial prototype through to production deployment.
• Knowledge of AI governance and compliance, including responsible AI principles, bias testing, and maintaining audit trails suitable for regulated industries.
• Databricks ecosystem — Unity Catalog, Model Serving, Feature Engineering, Mosaic AI Gateway, Lakebase
• Excellent communication skills, able to explain complex AI architectures to senior leaders while also collaborating deeply with engineering teams to troubleshoot technical issues.
• Other tech and skills we like, but isn't essential: Experience with agent tooling, including MCP servers, Unity Catalog functions, and tool orchestration patterns.
• Familiarity with evaluation frameworks such as Mosaic AI Agent Evaluation, Garak, or custom-built evaluation harnesses.
• Background in advanced machine learning, including deep learning with PyTorch, computer vision methods, NLP pipelines, or graph-based data processing.
• Knowledge of cloud infrastructure and modern deployment practices, including Terraform, Bicep, Kubernetes, and serverless architectures.
• Exposure to red teaming and AI security, such as adversarial testing, prompt‑injection defence, and working with compliance frameworks (e.g., NIST AI 600‑1, EU AI Act).
• Understanding of Agile delivery methodologies, including Scrum and Kanban.

Tech Stack

• Azure
• Cloud
• Kubernetes
• Python
• PyTorch
• Terraform
• Unity

Benefits

• Up to 15% discretionary bonus
• Industry matching Maternity & Paternity policy
• Private Medical & Dental Care plus Eye care scheme
• Health & Well-being supplement
• 25 Days Annual Leave, Birthday Leave & Charity Leave
• Away days with the team
• Flexible Working Hours
• Electric Car Scheme