Senior AI Engineer

Salary: £60,000 - 100,000 per year

Requirements:

• We need 6+ years of software engineering experience, with strong fundamentals in system design, data structures, and clean code practices.
• We need proven experience designing and shipping production-grade AI or ML-enabled software systems.
• We need strong proficiency in Python, including building and shipping production backend services.
• We need hands-on experience building applications with LLMs such as Azure OpenAI, OpenAI, Anthropic, or similar.
• We need experience with FastAPI or comparable Python web frameworks.
• We need production experience with Docker and Kubernetes, including deployment and management on AKS.
• We need strong hands-on experience with Azure, including Azure OpenAI, Azure AI Search, AKS, and Databricks.
• We need proven production experience with LangGraph and LangChain, including multi-step agentic workflows and tool-calling agents.
• We need hands-on experience with Azure AI Search or other vector/hybrid search solutions, including vector search, hybrid search, and retrieval evaluation.
• We need experience with Databricks and PySpark for large-scale data processing.
• We need experience designing evaluation frameworks for LLM systems, including offline metrics, hallucination detection, and production monitoring.
• We need experience implementing responsible AI practices in a regulated environment, including audit trails, confidence scoring, and human-in-the-loop controls.
• Background in traditional ML or data engineering, including feature pipelines, model training, and ETL, is preferred.
• MongoDB or other NoSQL database experience is preferred.
• Prior exposure to insurance domain concepts such as underwriting, claims, and policy administration is preferred.
• We need experience mentoring engineers, leading technical discussions, and influencing architecture decisions.
• We need strong problem-solving skills and the ability to work through ambiguity.
• We need the ability to balance speed of delivery with engineering quality and long-term maintainability.
• We need strong communication skills and the ability to explain technical concepts to both technical and non-technical stakeholders.
• We need a proactive mindset with ownership of outcomes and continuous improvement.
• We need interest in emerging AI technologies and practical application of LLMs in enterprise environments.

Responsibilities:

• We lead the design and build of end-to-end generative AI applications using LangGraph, including agentic workflows, RAG pipelines, and LLM-integrated services.
• We define and drive architecture for scalable, secure, reliable, and maintainable AI solutions deployed in production.
• We develop robust, well-tested backend APIs with FastAPI, containerized via Docker and deployed on Kubernetes.
• We architect and own search and retrieval solutions using Azure AI Search and MongoDB, including design of indexing strategies, hybrid search configurations, and retrieval evaluation.
• We work within our Azure cloud environment, integrating with Azure OpenAI, Azure services, and our broader data platform.
• We collaborate with product managers, data scientists, engineers, and other stakeholders to scope and deliver AI features that address real insurance business problems.
• We own the full software lifecycle, including design, code review, testing, deployment, monitoring, and production support.
• We translate complex business requirements into well-scoped technical solutions with a strong focus on reliability, maintainability, failure modes, and operational excellence.
• We mentor and support junior engineers through design reviews, code reviews, and technical guidance.
• We contribute to technical standards, best practices, and reusable patterns for AI engineering across the team.
• We evaluate and improve model quality, retrieval strategies, prompt and agent design, and production performance over time.
• We partner with business and technical leaders to shape AI roadmaps and identify high-impact opportunities for automation and decision support.
• We lead the delivery of high-impact AI solutions that are reliable, scalable, and production-ready.
• We help the team make better technical decisions through strong architecture and engineering judgment.
• We raise the quality bar through mentoring, code reviews, and engineering best practices.
• We contribute to a stronger AI engineering capability across the organization.

Technologies:

• AI
• Architect
• Azure
• Backend
• Cloud
• Databricks
• Docker
• ETL
• FastAPI
• Support
• Kubernetes
• LLM
• Model Training
• MongoDB
• NoSQL
• Python
• PySpark
• RAG
• Web

More:

We are Chubb, and we are looking for a Senior AI Engineer to help design, develop, and deploy advanced generative AI solutions that improve how we operate across the insurance lifecycle, from underwriting and claims to customer service and risk assessment. This role sits at the intersection of software engineering, applied AI, and technical leadership, and it is built on our Azure and Databricks platform. We offer a competitive salary and pension scheme, discretionary bonus scheme, 25 days annual leave plus the ability to purchase 5 additional days, hybrid working options, Private Medical cover, Employee Share Purchase Plan, Life Assurance, subsidised gym membership, comprehensive learning and development offerings, and an Employee Assistance Program. Our core values are integrity, client focus, respect, excellence, and teamwork. We are committed to an ethical, collaborative, and supportive working environment, and we value diversity and inclusion with an accessible recruitment process.

last updated 36 week of 2026