Director Productivity Suite Engineering

The CTO team at HSBC is seeking a visionary, hands-on engineering leader to oversee the delivery, operational performance and technical evolution of HSBC Productivity Suite (HPS), a portfolio of AI-enabled solutions that helps colleagues work more efficiently and create greater value for customers and the bank.

You’ll lead an inclusive, innovative and high-performing global engineering organisation, ensuring HPS remains reliable, secure, scalable and well controlled while improving the pace, safety and quality of delivery. Working with Product and wider technology team, you’ll turn business priorities into efficient and high-quality technical deliveries to improve workplace productivity powered by AI.

Responsibilities:

• Lead delivery of the HPS engineering roadmap, aligning priorities with product strategy, colleague needs and measurable outcomes.
• Partner with Product and stakeholders to translate business priorities into clear, and achievable technical plans.
• Lead a globally distributed engineering organisation, fostering an inclusive, collaborative and high-performing culture.
• Set the technical direction for HPS across applications, AI/Agentic AI, platforms, architecture, data, APIs and developer tooling.
• Ensure HPS is secure, scalable, reliable and resilient, with effective support, monitoring, incident management and continuous improvement.
• Embed strong engineering practices across software design, testing, automation, DevSecOps, observability, improving speed and quality while managing cost.
• Maintain robust technology, privacy, model-risk, cyber, compliance and operational controls.
• Build trusted relationships with senior stakeholders, communicating progress, risks and trade-offs clearly while enabling timely decisions and delivery.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related subject area.
• At least 10 years’ software engineering experience (with 5+ years of technical leadership role), including three or more years focused on AI/Agentic AI.
• Proven experience delivering and operating large-scale production systems, including GenAI applications.
• Strong technical expertise in LLM-based applications, personal agents, Retrieval-Augmented Generation (RAG), agentic workflows, model evaluation, safety guardrails and responsible AI.
• Hands-on experience with Python, APIs, microservices, databases, cloud platforms, containers and Kubernetes.
• Proven ability to build inclusive, high-performing teams, develop technical talent, make sound decisions and balance innovation with responsible, sustainable engineering.