Role overview
Role: Senior AI Engineer
Employment: Fulltime Location – London (Hybrid, 3 days per week on-site)
We are looking for a highly skilled Senior AI Engineer to work on the architecture, development, and productionisation of intelligent AI solutions. This will involve building software powered by Large Language Models (LLMs), Agentic frameworks, and predictive algorithms.
The ideal candidate blends software engineering discipline with a deep understanding of AI to design scalable, cost-efficient, highly reliable systems, and driving best-practice use of Databricks across the organisation.
This role sets the technical foundations, standards, and patterns that enable teams to build, deploy, and operate production-grade AI engineering solutions efficiently and safely. The role combines strong software engineering, deep Databricks knowledge, and AI expertise, with a focus on developer experience and scalability.
Responsibilities
- Analyse and interpret eval results, logs and traces from a live AI product
- Develop and maintain Python microservices, Azure functions, Python packages and REST APIs
- Build and maintain Lambda functions, Step Functions, and LLM agents to orchestrate workflows.
- Work with DevOps engineers on day-to-day development, deployment, and operational support.
- Contribute to CI/CD pipelines and deployment automation using GitHub Actions.
- Manage artifacts, enforce branch strategies, and utilize Maven and Nexus for release-to-live (RTL) development, including versioning, dependencies, and packaging standards.
- Participate in code reviews and maintain documentation for backend services.
Basic qualifications
- Hands-on experience with Python frameworks such as Flask, FastAPI, or Django.
- Proven experience building and maintaining RESTful APIs.
- Solid understanding of API design, security, versioning, and scalability.
- Python proficiency, LLM orchestration (RAG), and hands-on experience designing end-to-end intelligent applications using Microsoft's cloud ecosystem
- Familiarity with serverless architectures and event-driven design.
- Knowledge of model orchestration, prompt engineering and LLM evaluation workflows.
- CI/CD and Git-based workflow knowledge.
- Ability to ensure data consistency, logging, and error handling across distributed services.
- Experience with GitHub Actions, Jenkins, or other pipeline automation tools.
- Experience with LangChain, LangGraph and Vector databases.
- Degree in Computer Science, Software Engineering, or related field — or equivalent experience.
Preferred qualifications
- GenAI exposure