Sr. Associate Director, Software Engineering(Productivity Suite)

Spend more than half your time on hands-on engineering, writing, reviewing, testing and shipping production code for HSBC Productivity Suite. Design and build production-grade generative AI capabilities and integrations, taking ownership from initial design through deployment, operation and continuous improvement. Provide technical leadership across engineering pods, forming a clear technical vision, setting direction and breaking complex programmes of work into manageable deliveries. Make sound technical decisions across performance, security, cost, maintainability, technical debt, failure handling, observability, rollout safety and long-term operability. Shape technical strategy and roadmaps, influencing priorities and translating user needs and ambiguous business problems into measurable outcomes and practical engineering plans. Drive reusable capabilities, frameworks, engineering standards and effective technology controls, including monitoring and the safe use of AI coding tools and agents across the software development lifecycle. Raise engineering capability through pairing, design and code reviews, practical mentoring, knowledge-sharing and example-setting, without formal line-management responsibility. Lead continuous improvement in production stability, setting measurable goals to reduce incidents and recovery times and leading from the front during production issues. Deep, hands-on software engineering experience, with a strong record of designing, coding and operating user-facing products and distributed services at scale. Advanced use of AI coding tools, such as GitHub Copilot, to prototype, write, test and review code safely, alongside experience building agents that improve the software development lifecycle. Strong Python expertise and practical knowledge of modern engineering practices, including application programming interfaces, microservices, databases, containers, automated testing and continuous integration and delivery. Hands-on experience taking artificial intelligence, machine learning and generative AI solutions from experimentation through to secure, reliable production use. Strong practical knowledge of large language models, prompt engineering, retrieval-augmented generation, agentic workflows, evaluation, guardrails, observability and responsible AI. Strong engineering judgement, with the ability to balance performance, security, cost, resilience, maintainability, technical debt and delivery pace when making complex design decisions. Experience forming a technical vision, influencing business and engineering priorities, breaking complex work into manageable deliveries and raising standards through technical expertise rather than formal authority. Strong ownership, problem-solving and communication skills, with the ability to work autonomously across global and multicultural teams, explain technical trade-offs clearly and turn ambiguous problems into robust, measurable outcomes.