Associate Director, Software Engineering(Productivity Suite)

Spend most of your time on hands-on engineering, writing, reviewing, testing and shipping production code for HSBC Productivity Suite. Design and deliver significant generative AI capabilities and integrations, owning delivery from requirements through to production operation. Act as a senior engineer within an engineering pod, making sound design decisions, clarifying ambiguity and breaking complex requirements into actionable deliveries. Build secure, resilient and maintainable services, applying appropriate engineering controls across testing, deployment, monitoring, observability and production support. Use and improve shared frameworks, platforms and reusable capabilities, giving constructive feedback and reducing duplication and technical debt. Promote effective engineering practices, including the safe use of AI coding tools and agents to improve quality and delivery across the software development lifecycle. Take an active role in production incidents, helping restore service, leading reviews and ensuring lessons result in practical improvements. Mentor engineers through pairing, design and code reviews, knowledge-sharing and practical support, while informing technical direction through evidence and engineering expertise. Strong hands-on software engineering experience, with a record of designing, coding, testing and operating significant applications or product capabilities. Effective use of AI coding tools, such as GitHub Copilot, to prototype, write, test and review code safely, with an interest in 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 building AI, machine learning or generative AI solutions and taking them from experimentation into secure, reliable production use. Practical knowledge of large language models, retrieval-augmented generation, agentic workflows, evaluation, guardrails, observability and responsible AI. Sound engineering judgement across performance, security, resilience, maintainability, accessibility, technical debt and production operability. Ability to clarify ambiguous requirements, identify the most important parts of a problem and deliver robust solutions with limited oversight. Strong communication and collaboration skills, with the ability to explain technical decisions clearly, challenge constructively and mentor engineers in a global team.