SBS is seeking a skilled AI Engineer to join its Data & AI / Engineering organization in the UK or EU. This role will focus on designing, building, and deploying AI-driven solutions that enhance SBS products and client offerings. 

The ideal candidate will combine strong software engineering fundamentals with applied AI/ML expertise, enabling the development of scalable, production-grade AI systems in a regulated financial services environment. 

Location: UK or EU 

Hybrid/Remote: Remote (Ocasional travel required) 

Software Architecture & Design 

• Application architecture: Strong grasp of clean/hexagonal architecture, dependency injection, SOLID principles, and protocol-based interfaces. Can design well-structured Python services with clear separation of concerns, testable components, and maintainable codebases. This is not optional — the existing system follows these patterns and new code must be consistent. 

• API design: Experience designing and maintaining RESTful API contracts. Understands OpenAPI specifications, versioning strategies, schema evolution, and backward compatibility. Can own the API surface that internal consumers depend on. 

• System design: Distributed systems thinking — understands event-driven patterns, asynchronous communication, eventual consistency, and the trade-offs of different integration approaches. Can reason about how components interact across service boundaries. 

• Data modelling: Can design domain models, define data flows between system components, and make pragmatic schema design decisions. Understands how data structures affect downstream consumers and system evolution. 

AI & LLM Application Skills  

• LLM application development: Hands-on experience building production applications powered by LLMs. Must go beyond API calls — RAG pipelines, chain-of-thought reasoning, structured output parsing, multi-step workflows. Candidates who have only fine-tuned models or only called a single provider’s API do not qualify. 

• Model-agnostic design: This is a sovereign AI system. The candidate must design against standardised API interfaces (OpenAI-compatible, LiteLLM, or equivalent abstraction layers), not couple to any single provider. Must understand model routing, fallback strategies, and how to build systems that can swap underlying models without application-layer rewrites. Experience limited to a single commercial API (OpenAI, Google, Anthropic) without abstraction is insufficient. 

• Agentic system design: Demonstrated experience designing multi-step AI systems where the model makes decisions about what to do next. This could be via LangGraph, CrewAI, AutoGen, custom agent loops, or any framework — the underlying patterns (ReAct, plan-and-execute, reflection) matter more than the tool. 

• Prompt engineering depth: Can demonstrate iterative prompt development for complex tasks. Understands few-shot, chain-of-thought, XML/structured prompting, and the behavioural differences between model families and sizes. Critically, understands that prompt strategies must adapt when moving between frontier and smaller OSS models. 

Python Engineering 

Production Python: Strong async Python with FastAPI or equivalent framework. Comfortable with Pydantic for data validation, SQLAlchemy for data access, and structured logging (structlog). Writes clean, testable, well-documented code with proper type hints. This is a software engineering role that builds AI systems — not a data science role that happens to write Python.  Safeguards for hallucinated tools, loops, partial completion, unsafe actions. Understands async trade-offs, batching, streaming, latency accumulation 

Engineering Qualities  

• Works within existing systems: The candidate joins a substantial existing codebase and architecture. They must be comfortable reading, understanding, and extending code they did not write — not lobbying to rewrite it. 

• Production mindset: Thinks about error handling, retry logic, graceful degradation, observability, and security as first-class concerns. Understands that agentic autonomy creates new failure modes that must be anticipated. 

• Clear communicator: Can explain technical trade-offs to non-technical stakeholders. Can write clear design documents. Can articulate why an agentic approach is or is not appropriate for a given problem. 

#LI-KJ1 

#LI-Remote 

At SBS, we’re more than just a technology company, we’re a global fintech partner helping banks and financial institutions transform, innovate, and grow. With over 5,000 employees worldwide and clients in more than 80 countries, our solutions power everything from digital banking and lending to payments and core banking systems.

As part of 74Software, we’re backed by a group of leading software companies delivering mission-critical solutions worldwide. Our focus is on delivering long-term value, leveraging cutting-edge technology, and fostering strong client partnerships. Join us and be part of a collaborative, forward-thinking team shaping the future of finance.

Why SBS?

At SBS, we’re committed to supporting our employees in every aspect of their lives, from health and wellbeing to financial security and lifestyle perks.

We offer benefits that allow you to thrive at work and beyond, including health coverage, retirement plans, paid time off, flexible work, career development, competitive pay, and global culture perks.

Equal Opportunity Employer

We are committed to providing equal opportunities and ensuring a fair and inclusive recruitment process. We do not discriminate on the basis of age, disability, gender, sexual orientation, race, religion, or any other protected characteristic.