Principal AI Engineer

Job Summary

The Principal AI Engineer is responsible for designing, building, and operating the data pipelines and data infrastructure that power AI, machine learning, and agentic applications across the Bank. The role owns the end-to-end data lifecycle from ingestion and integration through transformation, semantic enrichment, and retrieval-ready delivery.

This role partners closely with data, engineering, AI, and platform teams to create scalable, reliable, and governed data foundations that support AI-driven products and intelligent automation. The successful candidate combines deep expertise in large-scale data engineering, distributed processing, semantic modelling, and modern data architecture with the ability to design systems that balance scalability, performance, resilience, and cost.

Key Responsibilities

Strategy

• Drive the design and evolution of the Bank's AI data architecture and data engineering standards.
• Define scalable patterns for ingestion, transformation, enrichment, storage, and retrieval of structured and unstructured data.
• Contribute to enterprise data standards, semantic modelling frameworks, and reusable architecture blueprints supporting AI adoption.
• Partner with architecture, platform, and AI teams to shape the future data ecosystem for AI and agentic applications.

Business

• Design, build, and operate data pipelines supporting AI, machine learning, analytics, and agent-based use cases.
• Deliver trusted, high-quality datasets that support model training, retrieval, feature generation, and operational AI workloads.
• Enable integration across databases, APIs, event streams, cloud platforms, document repositories, and external data sources.
• Collaborate with AI engineers, data scientists, architects, and business stakeholders to deliver scalable data solutions.

Processes

• Develop and maintain batch and streaming data pipelines using distributed processing technologies.
• Design and optimise data workflows running on lakehouse platforms and distributed compute environments.
• Build retrieval-ready and feature-ready datasets for AI and machine learning applications.
• Develop semantic layers, ontologies, taxonomies, and knowledge representations that improve data discovery and AI reasoning.
• Design solutions leveraging graph databases, vector stores, document stores, and other non-relational technologies.
• Implement data quality controls, lineage, observability, monitoring, and operational support processes.
• Support ingestion, parsing, chunking, enrichment, and normalisation of unstructured and multimodal content.

Risk Management

• Apply security, governance, privacy, and data protection controls throughout the data lifecycle.

• Ensure data engineering solutions align with enterprise governance, regulatory requirements, and operational resilience standards.
• Promote strong data quality, traceability, auditability, and reliability practices across data platforms.

Governance

• Contribute to enterprise standards for AI-ready data architecture and engineering practices.
• Maintain documentation, architecture artefacts, engineering standards, and operational runbooks.
• Support architecture reviews and technology governance processes.

Regulatory & Business Conduct

• Display exemplary conduct and live by the Group's Values and Code of Conduct.
• Take personal responsibility for embedding the highest standards of ethics, regulatory compliance, and business conduct.
• Effectively identify, assess, escalate, mitigate, and resolve risk, conduct, and compliance matters associated with data platforms and AI solutions.

• Ensure data engineering solutions align with enterprise governance, regulatory requirements, and operational resilience standards.
• Promote strong data quality, traceability, auditability, and reliability practices across data platforms.

Our Ideal Candidate

•    12+ years of experience in data engineering, software engineering, data platforms, or distributed systems, with a strong track record of delivering enterprise-scale data solutions.
•    Proven experience building and operating large-scale batch and streaming data pipelines supporting critical business workloads.
•    Strong expertise in Spark, Databricks, or equivalent distributed compute platforms, including performance optimisation, workload tuning, and operational support.
•    Experience designing data platforms using lakehouse architectures, object storage, and modern data formats including Parquet, Delta Lake, or Iceberg.
•    Strong understanding of data modelling and storage technologies, including graph databases, vector databases, document stores, key-value stores, and wide-column databases.
•    Experience building data integration solutions across databases, APIs, event streams, files, and cloud-native platforms.
•    Knowledge of ontology development, semantic modelling, taxonomies, RDF, knowledge graphs, or property graph technologies.
•    Experience processing and transforming unstructured and multimodal content into AI-ready datasets.
•    Strong understanding of system design concepts including throughput, latency, consistency, idempotency, resiliency, and cost optimisation.
•    Experience with AI, machine learning, feature engineering, retrieval architectures, or agentic applications provides additional value.
•    Strong analytical thinking, problem-solving skills, and a collaborative engineering mindset.
•    Degree in Computer Science, Engineering, Data Engineering, Information Systems, or a related discipline. Equivalent practical experience is equally valued. 

Role Specific Technical Competencies

•    Data Engineering & Data Pipelines
•    Apache Spark & Distributed Processing
•    Databricks & Lakehouse Architecture
•    Object Storage (ADLS, S3, MinIO)
•    Data Modelling & Data Architecture
•    Graph Databases & Knowledge Graphs
•    Vector Databases & Retrieval Systems
•    NoSQL Data Platforms
•    Streaming Technologies (Kafka, Kinesis, Pulsar)
•    Data Integration & API Engineering
•    Semantic Modelling, RDF & Ontologies
•    AI/ML Data Preparation & Feature Engineering
•    Unstructured Data Processing
•    Data Governance, Observability & Lineage
•    Performance Optimisation & System Design
•    Cloud Data Platforms (Azure & AWS)

About Standard Chartered

We're an international bank, nimble enough to act, big enough for impact. For more than 170 years, we've worked to make a positive difference for our clients, communities, and each other. We question the status quo, love a challenge and enjoy finding new opportunities to grow and do better than before. If you're looking for a career with purpose and you want to work for a bank making a difference, we want to hear from you. You can count on us to celebrate your unique talents and we can't wait to see the talents you can bring us.

Our purpose, to drive commerce and prosperity through our unique diversity, together with our brand promise, to be here for good are achieved by how we each live our valued behaviours. When you work with us, you'll see how we value difference and advocate inclusion.

Together we:

• Do the right thing and are assertive, challenge one another, and live with integrity, while putting the client at the heart of what we do
• Never settle, continuously striving to improve and innovate, keeping things simple and learning from doing well, and not so well
• Are better together, we can be ourselves, be inclusive, see more good in others, and work collectively to build for the long term

What we offer

In line with our Fair Pay Charter, we offer a competitive salary and benefits to support your mental, physical, financial and social wellbeing.

• Core bank funding for retirement savings, medical and life insurance, with flexible and voluntary benefits available in some locations.
• Time-off including annual leave, parental/maternity (20 weeks), sabbatical (12 months maximum) and volunteering leave (3 days), along with minimum global standards for annual and public holiday, which is combined to 30 days minimum.
• Flexible working options based around home and office locations, with flexible working patterns.
• Proactive wellbeing support through Unmind, a market-leading digital wellbeing platform, development courses for resilience and other human skills, global Employee Assistance Programme, sick leave, mental health first-aiders and all sorts of self-help toolkits
• A continuous learning culture to support your growth, with opportunities to reskill and upskill and access to physical, virtual and digital learning.
• Being part of an inclusive and values driven organisation, one that embraces and celebrates our unique diversity, across our teams, business functions and geographies - everyone feels respected and can realise their full potential.

Recruitment Assessments

Some of our roles use assessments to help us understand how suitable you are for the role you've applied to. If you are invited to take an assessment, this is great news. It means your application has progressed to an important stage of our recruitment process.

Visit our careers website www.sc.com/careers