Securities Services Tech - Sr. Associate Director - AI Engineering Lead

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HSBC is one of the largest banking and financial services organisations in the world, with operations in 64 countries and territories. We aim to be where the growth is, enabling businesses to thrive and economies to prosper, and, ultimately, helping people to fulfil their hopes and realise their ambitions.

We are currently seeking an experienced professional to join our team in the role of Sr. Associate Director – Artificial Intelligence Engineering Lead in the CIB Tech – Securities Services & Digital Assets Technology department.

Securities Services and Digital Assets Technology is scaling the use of Artificial Intelligence from experimentation to production. This role offers the opportunity to build the engineering foundations, reusable patterns and production-grade solutions that allow Artificial Intelligence to deliver real value for our clients and colleagues.

As the Artificial Intelligence Engineering Lead, you’ll lead a team that designs, builds and runs Artificial Intelligence solutions end to end – from the data that feeds them, through model and agent design, to secure deployment, monitoring and continuous improvement in production. You’ll focus on Generative Artificial Intelligence and Large Language Model applications, including Retrieval Augmented Generation, document and unstructured data processing, and agent-based automation of operational workflows.

Working across Technology, Operations, Product, Data, Architecture, Risk and Control teams, you’ll turn business problems into engineered, measurable solutions. The role will suit a hands-on engineering leader who pairs deep technical craft with sound judgement – someone who understands that Artificial Intelligence in a regulated environment must be not only capable, but explainable, controlled and dependable.

Role: Sr. Associate Director – Artificial Intelligence Engineering Lead

In this role, you will:

• Lead the design, build and production delivery of Artificial Intelligence solutions, with a strong emphasis on Generative Artificial Intelligence and Large Language Model applications such as Retrieval Augmented Generation, unstructured document processing, summarisation and agent-based workflow automation.
• Set the engineering standards, reusable frameworks and reference architectures for Artificial Intelligence development, covering prompt and context design, orchestration, tool integration, evaluation, testing, observability and cost efficiency.
• Own the Artificial Intelligence engineering lifecycle end to end, including data readiness, model and solution selection, secure deployment, monitoring, feedback loops and continuous improvement in production.
• Partner with data engineering and platform teams to build Artificial Intelligence ready data foundations – pipelines, feature and vector stores, retrieval layers, lineage and data quality controls that make enterprise information usable and trustworthy.
• Embed Responsible Artificial Intelligence by design, working with Risk, Compliance, Model Risk Management, Legal and Cyber Security teams on governance, model documentation, bias and safety testing, human oversight, data privacy and regulatory expectations.
• Shape and qualify Artificial Intelligence propositions with business, product and operations stakeholders – assessing feasibility, defining success measures, building the technical case and guiding use cases from concept to adoption at scale.
• Build, coach and grow a high-performing engineering team, raising Artificial Intelligence and software engineering capability through code review, pairing, knowledge sharing and clear technical direction.
• Define and track measurable outcomes, including reduced manual processing, faster access to information, improved data quality, increased straight-through processing, stronger control effectiveness and demonstrable client and colleague benefit.
• Strong, hands-on engineering experience building and running Artificial Intelligence and Machine Learning solutions in production, with proven depth in Python and modern software engineering practice.
• Demonstrable experience delivering Generative Artificial Intelligence and Large Language Model applications, including Retrieval Augmented Generation, embeddings and vector search, prompt and context engineering, agent or tool-calling patterns, and systematic evaluation of model outputs.
• Practical experience of Machine Learning Operations and Large Language Model Operations – continuous integration and continuous delivery, containerisation, orchestration, cloud-based deployment, observability, drift and quality monitoring, and cost and performance optimisation.
• Solid data engineering foundations, including distributed data processing, application programming interface and event-driven integration, data modelling, lineage and data quality controls for Artificial Intelligence ready data platforms.
• Sound understanding of Responsible Artificial Intelligence and governance in a regulated environment, covering model risk management, explainability, safety and bias testing, data privacy, security and human oversight.
• Experience leading or mentoring engineering teams, setting technical direction and raising engineering quality, with the ability to remain hands-on in code and architecture.
• Ability to translate complex business and operational needs into clear technical designs, delivery plans and success measures, and to communicate trade-offs credibly to technical and non-technical audiences.
• A collaborative, pragmatic and commercially minded approach, with sound judgement and a strong focus on client outcomes, operational resilience, control effectiveness and sustainable delivery.

You’ll achieve more when you join HSBC.

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Issued by – HSBC Software Development India