Senior AI Engineer

We are seeking an experienced Senior AI Engineer to join our AI Engineering squad as we scale our in-house artificial intelligence capability across Shawbrook Bank. You will join at a pivotal stage of our AI transformation, as we move from experimentation and proof-of-concept initiatives into production-grade AI systems that deliver measurable business value across lending, deposits, operations, risk, and customer experience. Working in close partnership with our AI Product Manager and alongside the AI Engineering Lead, you will design, build, deploy, and operate robust, secure, and compliant AI solutions within a regulated banking environment. This is a hands-on, high-impact role for an engineer who wants to own things end-to-end. You will take AI products and shared platform capabilities from prototype through to production, and you'll take on some of our most demanding technical challenges. Chief among them is retrieval-augmented generation (RAG) at scale: building retrieval and generation pipelines that stay accurate, fast, and cost-effective across large corpora. You will also help raise the bar for how the whole team builds — embedding the controls production AI needs, such as evaluation, observability, and responsible-AI guardrails. You’ll also be mentoring other engineers as the team grows. Key Responsibilities - Design, build, and operate end-to-end AI systems (LLM/RAG pipelines, retrieval, and agentic workflows) from prototype through to production. - Own AI products and shared, reusable platform capabilities end-to-end, enabling teams across the Bank to adopt AI without building from scratch. - Develop deep expertise in our AI platform and applications, with a good working understanding of other domains across the Bank (lending, data, risk, and operations). - Tackle our hardest technical problems, in particular retrieval-augmented generation at scale across large corpora. - Build and maintain the controls that production AI depends on (evaluation frameworks, observability, testing, and CI/CD). - Embed responsible-AI principles (explainability, guardrails, and appropriate governance) within a regulated environment. - Design well-documented, self-service APIs that other teams can adopt independently. - Lead projects independently, unblocking your own work and unblocking others across the team. - Mentor and support other AI Engineers through pairing, code review, and pragmatic engineering standards. - Support engineers in the wider Shawbrook Engineering department with AI adoption and upskilling. - Work within an agile, cross-functional squad to deliver iteratively and aligned to business value. Essential - You have designed, built, and deployed LLM and machine-learning systems in production, ideally including retrieval-augmented generation (RAG). - Confident building backend services and APIs in Python, with sound testing, observability, and CI/CD practices. - Experience delivering on a major cloud platform, preferably Azure. - Comfortable evaluating AI systems for accuracy and reliability, and with the controls needed to run them responsibly. - You can take work from idea to production independently and enjoy owning it end-to-end. - Experience mentoring and leading others. - Relevant academic background in Computer Science, Data Science, Engineering, Mathematics, or related discipline. Nice to have - Experience with semantic or vector search at scale, including performance and cost tuning. - Professional certifications in cloud platforms (e.g., Azure AI Engineer Associate) would be beneficial. - Background in machine learning engineering/operations. - Exposure to .NET (some of our services are .NET-based). - Experience in regulated environments.