AI Data Engineer in London

The AI and Innovation department delivers robust, scalable, and secure AI solutions across bank's global platforms, acting as a business-facing service provider dedicated to advanced technology, operational excellence, and innovation.

This group supports the bank's extensive footprint in Asia, the Americas, and other regions.

AI and Innovation department is responsible for maintaining a comprehensive catalogue of AI products and services.

In addition, the function is managing the portfolio of end user managed applications (EUMA) platforms ensuring these applications - created and maintained directly by business units - are governed with proper oversight, operational resilience, and alignment to technology and risk management frameworks.

This includes supporting innovation at the user level while balancing regulatory obligations and operational continuity.

Alongside operational responsibilities, the department drives innovation, modernisation, and strategic transformation within the AI landscape, ensuring the adoption of cutting-edge technologies and compliance with global control and regulatory frameworks.

• The AI and Data Engineer role is responsible for designing, building, and operating data pipelines, data products and AI-enabled engineering components that prepare, govern and serve data for analytics, automation and enterprise AI solutions.
• The role combines strong data engineering discipline with hands-on AI engineering capability, including designing, developing and productionising AI-enabled solutions using retrieval-augmented generation, embeddings, vector search, context/prompt engineering, agentic AI patterns, MCP-based extensibility, and Microsoft ecosystem AI tooling.

The role ensures these solutions are grounded in reliable, well-governed and secure data foundations.

• What you’ll be doing
• Design, build and operate scalable data pipelines and reusable data assets to support analytics, automation and AI use cases.
• Implement data models, transformations and serving patterns that improve consistency, reusability, quality and performance.
• Apply enterprise patterns for ingestion, storage, processing and serving, including Lakehouse/medallion layering, metadata enrichment and standardised data access APIs.
• Engineer solutions for resilience, observability, cost-efficiency and maintainability across production environments.
• Design and implement custom AI-enabled systems and components, including retrieval-augmented generation, MCP-based extensibility, agentic AI architectures, embeddings, vector-based retrieval and context/prompt engineering.
• Build and productionise AI solutions using the Microsoft ecosystem, including Azure-based AI engineering, M365 Copilot extensibility and Power Platform, where appropriate.
• Integrate AI-enabled components into enterprise systems and software, ensuring technical fit, operational resilience and alignment with production support expectations.
• Develop data access, indexing, metadata enrichment and retrieval patterns needed to connect enterprise data with AI solutions in a secure and controlled way.
• Design AI-facing data services with strong operational controls, observability, disaster recovery and business continuity considerations.
• Produce high-quality engineering artefacts, including solution designs, technical documentation, test evidence, runbooks and operational guides reflecting best-practice AI and data engineering design.
• Data Pipelines, Operations & Support
• Develop and operate end-to-end pipelines across ingestion, validation, transformation, enrichment and serving.
• Ensure data quality, completeness and timeliness through automated checks, reconciliation, error handling and remediation.
• Implement orchestration, scheduling, monitoring, alerting, recovery mechanisms and production support runbooks.
• Provide 2nd/3rd line support, assist with incident resolution and continually improve operational stability and performance.
• Security, Governance & Controls
• Embed secure data access mechanisms and fine-grained controls directly into pipelines, data products and AI-facing services.
• Implement lineage, auditability, provenance, privacy and retention controls consistent with internal standards and regulatory expectations.
• Support AI governance activities by maintaining clear documentation, control evidence and monitoring inputs for data-enabled AI solutions.
• Collaborate with Cybersecurity, Technology Risk, Data Governance and Architecture to ensure controls are embedded across the data and AI lifecycle.
• Work with Architecture to align solutions with enterprise reference architectures, AI patterns and data platform standards.
• Collaborate with data owners, SMEs, AI Engineers and delivery teams to turn business requirements into engineered solutions.
• Contribute to the evolution of data engineering, AI engineering and responsible delivery standards, patterns and best practices.
• Operate within an engineering function supporting multiple business domains, AI initiatives and transformation priorities.
• What you’ll need to be successful

We're looking for the following skills and experience. If you don't have all of these but think you could be a good fit for the role, get in touch.

• Strong experience designing, building and operating production-grade data pipelines, data assets and data services in enterprise environments.
• Solid understanding of data modelling, schema design, transformation patterns and data quality management for analytical and operational workloads.
• Knowledge of Lakehouse patterns, medallion concepts, metadata practices and scalable data processing across structured, semi-structured and unstructured data.
• Demonstrated hands-on experience designing and delivering enterprise-scale AI or Gen AI solutions.
• Strong working knowledge of AI/ML, NLP, LLMs, embeddings, agentic systems, RAG, MCP-based extensibility and associated design patterns.
• Practical experience building AI-enabled solutions using Microsoft enterprise stack and Azure-based AI tooling.
• Ability to engineer AI-ready data services through reliable data preparation, indexing, access control, metadata enrichment, context engineering and integration with enterprise systems.
• Exposure to CI/CD pipelines, testing frameworks, orchestration, observability, model governance, AI evaluation and monitoring practices.
• Strong understanding of data access controls, role-based and fine-grained access models, lineage, provenance, auditability, security, privacy and responsible AI controls.
• Proven ability to deliver practical data and AI engineering solutions in complex cross-functional environments, balancing delivery speed with resilience, control and long-term maintainability.

Why should you join us?

ICBC Standard Bank Plc (ICBCS) is a leading financial markets and commodities bank, driven to deliver the right outcomes for our stakeholders, clients, counterparties and markets.

We benefit from a unique Chinese and African parentage and an unrivalled global network and expertise.

We're headquartered in London, with operations in Shanghai, Singapore and New York.

We're a diverse and close-knit global team.

We put people first, giving talented, self-driven professionals the flexibility, rewards and freedom to grow their expertise and realise their potential.

Our vision statement, "Be Yourself, Succeed Together" underpins our drive for an open and transparent culture which values difference, enabling everyone to thrive whilst being themselves.

We have an active E, D&I forum and we're growing other employee network groups, including for women and neurodiversity.

We're committed to the principle of equal opportunities. All applicants will be treated equally and will be considered on their merits and skills without discrimination.

What's in it for you?

• Financial - market-based pay based on skills and experience, discretionary annual bonus, pension contribution 10% (employee contribution 5%), travel insurance, life assurance and income replacement insurance.
• Hybrid working - the option to work remotely up to two days per week, depending on the role.
• Family - 6 months maternity leave at full pay, 4 weeks paternity leave at full pay and enhanced shared parental leave pay.

Coaching for family leave returners and access to emergency care via My Family Care.

Paid fertility and miscarriage leave.

• Wellbeing - private medical insurance, Bike2Work scheme, health and fitness subsidy, holiday exchange, Employee Assistance Programme and menopause policy.
• Community - paid volunteering leave and Give As You Earn scheme. Vibrant CSR and engagement forums and fundraising for our charity partners.
• Development - a suite of opportunities to build the skills you need to excel in your role
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