At a Glance
- Tasks: Design and deploy AI solutions that revolutionise financial services.
- Company: Join a global fintech leader transforming banking with innovative technology.
- Benefits: Enjoy competitive pay, health coverage, flexible work options, and career development.
- Other info: Collaborative culture with excellent growth opportunities in a dynamic environment.
- Why this job: Make a real impact in finance while working with cutting-edge AI technologies.
- Qualifications: Strong software engineering skills and experience in AI/ML applications.
The predicted salary is between 60000 - 80000 £ per year.
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 (Occasional travel required)
Responsibilities:
- AI Solution Development: Design, build, and deploy AI/ML models and intelligent applications across SBS platforms. Develop solutions leveraging Machine Learning (ML), Natural Language Processing (NLP), and Generative AI (GenAI / LLMs). Translate business requirements into technical AI solutions that deliver measurable impact.
- Model Deployment & MLOps: Implement and manage end-to-end ML pipelines, from data ingestion to model deployment and monitoring. Collaborate with DevOps and engineering teams to ensure scalable, reliable production deployment. Maintain and optimize model performance, accuracy, and efficiency over time.
- Product Integration: Integrate AI capabilities into core banking, payments, and digital platforms. Work closely with Product Managers, Architects, and Developers to embed AI into customer-facing solutions. Support API development and microservices architecture for AI-driven features.
- Data Engineering Collaboration: Partner with data engineers to ensure data quality, availability, and pipeline integrity. Work with structured and unstructured datasets across large-scale, distributed systems.
- Innovation & Continuous Improvement: Stay current with advancements in AI, GenAI, and emerging technologies. Contribute to experimentation, prototyping, and innovation initiatives. Identify opportunities to improve automation, efficiency, and decision-making through AI.
Qualifications:
- Software Architecture & Design: 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. Experience designing and maintaining RESTful API contracts. Understands OpenAPI specifications, versioning strategies, schema evolution, and backward compatibility. 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. Can design domain models, define data flows between system components, and make pragmatic schema design decisions.
- AI & LLM Application Skills: 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. This is a sovereign AI system. The candidate must design against standardized API interfaces (OpenAI-compatible, LiteLLM, or equivalent abstraction layers). Demonstrated experience designing multi-step AI systems where the model makes decisions about what to do next. Can demonstrate iterative prompt development for complex tasks.
- Python Engineering: 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. Safeguards for hallucinated tools, loops, partial completion, and unsafe actions.
- Engineering Qualities: The candidate joins a substantial existing codebase and architecture. They must be comfortable reading, understanding, and extending code they did not write. Thinks about error handling, retry logic, graceful degradation, observability, and security as first-class concerns. Can explain technical trade-offs to non-technical stakeholders. Can write clear design documents.
Company Overview: 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. 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 help you thrive at work and beyond, including health coverage, retirement plans, paid time off, flexible work options, 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.
Artificial Intelligence Engineer employer: SBS
Contact Detail:
SBS Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Artificial Intelligence Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, GitHub contributions, or any relevant work. This gives you a chance to demonstrate your expertise beyond just a CV.
✨Tip Number 3
Prepare for interviews by practising common AI-related questions and coding challenges. Mock interviews with friends or using online platforms can help you feel more confident and ready to impress.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at SBS.
We think you need these skills to ace Artificial Intelligence Engineer
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the AI Engineer role. Highlight your experience with AI/ML, Python, and any relevant projects that showcase your skills. We want to see how you can bring value to our team!
Showcase Your Technical Skills: Don’t just list your skills; demonstrate them! Include specific examples of AI solutions you've developed or contributed to, especially those involving LLMs or MLOps. This helps us understand your hands-on experience and problem-solving abilities.
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language and avoid jargon unless necessary. We appreciate a well-structured application that makes it easy for us to see your qualifications at a glance.
Apply Through Our Website: We encourage you to submit your application directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, you’ll find all the details about the role and our company culture there!
How to prepare for a job interview at SBS
✨Know Your AI Fundamentals
Make sure you brush up on your AI and ML fundamentals before the interview. Be ready to discuss your experience with machine learning models, natural language processing, and generative AI. Prepare examples of how you've applied these technologies in real-world scenarios, especially in regulated environments.
✨Showcase Your Software Engineering Skills
Since this role requires strong software engineering fundamentals, be prepared to demonstrate your knowledge of clean architecture, API design, and distributed systems. Bring examples of your past projects that highlight your ability to write clean, maintainable code and how you've tackled challenges in system design.
✨Communicate Clearly
During the interview, focus on articulating your thought process clearly. You’ll need to explain complex technical concepts to non-technical stakeholders, so practice breaking down your ideas into simple terms. This will show that you can bridge the gap between technical and non-technical teams effectively.
✨Stay Current with AI Trends
Demonstrate your passion for AI by discussing recent advancements and trends in the field. Be ready to share your thoughts on emerging technologies and how they could impact the financial services industry. This shows that you're not just knowledgeable but also proactive about continuous learning and innovation.