AI Engineer - Banking
AI Engineer - Banking
A leading international bank is looking to appoint an AI Engineer to help deliver secure, governed and production-ready AI, data and automation solutions across its Front Office, operations, risk and control functions.
This is a broad, hands-on engineering role covering the full AI solution life cycle, from data preparation and prototyping through to deployment, monitoring, governance and operational handover.
You will work within the bank's Technology function and alongside its emerging AI Centre of Excellence, helping turn business ideas and early-stage prototypes into practical, scalable and controlled production solutions.
Key responsibilities
- Design, build and maintain data pipelines and curated datasets supporting AI, analytics, reporting and automation use cases.
- Develop AI-enabled solutions using generative AI, retrieval-augmented generation, predictive analytics, workflow automation and agentic AI.
- Build secure integrations between internal systems, databases, APIs, document repositories, market data providers and approved AI platforms.
- Work with business stakeholders, Technology, Risk and Compliance to identify and deliver high-value AI use cases.
- Help move AI prototypes into governed, maintainable and production-ready environments.
- Build dashboards and management information using Power BI or similar tools.
- Support model governance, including testing, documentation, monitoring, approval evidence, data quality and human-in-the-loop controls.
- Apply appropriate development, source control, testing, release management and support handover practices.
- Produce reusable technical documentation, runbooks and engineering patterns.
Experience required
- At least two years' experience in AI engineering, data engineering, analytics engineering, software engineering, BI development or automation.
- Strong Python and SQL skills.
- Experience building data pipelines, APIs, automation scripts or analytical datasets.
- Experience with Snowflake or a comparable cloud data platform.
- Practical experience using Power BI, DAX, Power Query or similar reporting tools.
Hands-on exposure to AI and machine learning technologies, which may include:
- LLM APIs
- Prompt engineering
- Retrieval-augmented generation
- Agentic workflow frameworks
- Python machine learning libraries
- Model testing and evaluation
- Understanding of the full solution life cycle, including development, testing, deployment, monitoring and production support.
- Experience using GitHub or an equivalent source control platform.
- Strong communication skills and the ability to translate business requirements into practical technical solutions.
Experience within banking, asset management, financial services or another regulated environment would be advantageous, as would an understanding of responsible AI, model governance, information security and data privacy.
The opportunity
This is an opportunity to join a growing AI capability at an early stage and help shape how AI solutions are designed, governed and deployed across an international banking organisation.
The role would suit an AI Engineer, Data Engineer or Analytics Engineer with strong Python and data engineering fundamentals who is looking to build practical, production-focused AI solutions within a regulated environment.
AI Engineer, AI & Data Engineer, Generative AI Engineer, GenAI Engineer, Machine Learning Engineer, Data Engineer, Analytics Engineer, Python, SQL, Snowflake, data pipelines, ETL, ELT, APIs, REST APIs, LLM, large language models, LLM APIs, OpenAI, Azure OpenAI, prompt engineering, retrieval augmented generation, RAG, vector databases, embeddings, LangChain, LlamaIndex, agentic AI, AI agents, workflow automation, machine learning, model evaluation, model monitoring, MLOps, Power BI, DAX, Power Query, data modelling, data quality, data lineage, GitHub, Git, CI/CD, model governance, responsible AI, AI governance, information security, data privacy, financial services, banking, asset management, regulated environment.