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We are currently seeking an experienced professional to join our team in the role of Sr. Associate Director, Software Engineering.

Business: Digital Platforms

Principal responsibilities

Applied AI for Engineering Productivity (Design/Coding/Testing)

• Identify high-impact opportunities to use AI to improve mobile engineering outcomes across design, coding, testing, release readiness, and incident response.
• Build and operationalise AI-assisted workflows for engineers (e.g., code generation and refactoring support, test case generation, defect triage, documentation automation, release note drafting), ensuring strong governance and quality controls.
• Develop AI-powered accelerators and reusable components (e.g., prompt patterns, evaluators, automation scripts, agentic workflows) that teams can adopt with minimal friction.
• Establish practical guidance for how we use AI here for common engineering tasksbalancing speed with correctness, security, and maintainability.

Data Engineering & Mobile Data Products

• Design, build, and maintain reliable data pipelines and curated datasets using mobile-related data sources such as: app telemetry, crash logs, performance metrics, network traces, CI/CD signals, test execution, feature usage analytics, customer journeys, and support/incident data.
• Define data models that enable consistent, trusted reporting and AI use cases (e.g., quality and stability KPIs, release health, funnel analysis, defect leakage, performance regression tracking).
• Implement data quality checks, lineage, monitoring, and documentation so stakeholders can trust and reuse the data confidently.
• Collaborate with security and risk partners to ensure compliant data handling, access controls, and responsible use of customer and operational data.

Dashboards & Decision Intelligence (Data-Driven Mobile)

• Build dashboards and decision tools that make excellent use of mobile-related dataturning metrics into insights and insights into actions.
• Create single pane of glass views for mobile engineering health (stability, performance, delivery, quality, customer impact), with clear definitions and drill-down paths.
• Enable proactive management through leading indicators and alerting (e.g., early detection of regressions, risk signals before release, anomaly detection in crash/performance patterns).
• Partner with mobile leadership to define KPIs that matter, establish targets, and drive measurable improvement over time.

AI Evangelism & Engineering Community Enablement

• Evangelise practical AI usage across the engineering community: run enablement sessions, publish playbooks, demo reusable patterns, and mentor teams to adopt AI safely and effectively.
• Build a culture of experimentation with disciplineencouraging rapid learning while maintaining engineering standards and auditability.
• Act as a trusted advisor to squads: helping them select tools, structure workflows, evaluate outputs, and avoid common AI pitfalls (hallucinations, overconfidence, data leakage, bias).
• Create internal documentation, FAQs, and troubleshooting guides to accelerate adoption and reduce repeated effort.

AI-Native Operating Model Support (Partnering with Mobile CTO)

• Support the Mobile CTO in shaping an AI-native engineering strategy: identifying the right problems to solve, prioritising investments, and tracking value delivered.
• Define lightweight governance that enables innovation while ensuring safe use (e.g., model/tool selection guidance, prompt/data handling standards, evaluation practices, human-in-the-loop controls).
• Establish measurement frameworks to quantify impact: cycle time reduction, defect reduction, test coverage improvements, incident reduction, customer experience improvements, and cost efficiency.
• Collaborate cross-functionally to ensure AI adoption aligns with architecture, security, compliance, and broader technology strategy.

Requirements

Essential

• Proven ability to use AI effectively to solve real engineering problems (design, coding, testing, analysis, automation), with a pragmatic and outcomes-focused mindset.
• Strong problem-solving abilities, including diagnosing ambiguous issues and translating them into data/AI solutions that ship.
• Excellent communication skills (written and verbal), able to influence and enable engineers and leaders across teams.
• Strong experience building production-grade data pipelines and datasets, with attention to reliability, observability, and data quality.
• Proven ability to build dashboards/analytics products that drive action, not just reporting.
• Strong understanding of secure data handling and engineering practices appropriate for a regulated environment.
• Experience working in Agile delivery environments and collaborating across product, engineering, and risk/security stakeholders.

Strong Technical Skills (AI/Data Engineering)

• Proficiency in Python and SQL for data engineering and applied AI workflows.
• Hands-on experience with AI tooling (e.g., LLMs and prompt engineering, retrieval-augmented generation concepts, evaluation techniques, agentic/automation workflows), and the discipline to validate outputs.
• Experience with analytics and visualisation tools (e.g., Power BI, Tableau, Looker, Grafana, or equivalent) and designing metrics that are well-defined and trustworthy.
• Familiarity with CI/CD and developer toolchains, and ability to integrate data/AI into engineering workflows (e.g., Git-based pipelines, test systems, build tooling).
• Understanding of experimentation and measurement (A/B testing concepts, KPI definition, causal thinking, guardrails).

Youll achieve more when you join HSBC.

HSBC is an equal opportunity employer committed to building a culture where all employees are valued, respected and opinions count. We take pride in providing a workplace that fosters continuous professional development, flexible working and, opportunities to grow within an inclusive and diverse environment. We encourage applications from all suitably qualified persons irrespective of, but not limited to, their gender or genetic information, sexual orientation, ethnicity, religion, social status, medical care leave requirements, political affiliation, people with disabilities, color, national origin, veteran status, etc., We consider all applications based on merit and suitability to the role.

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***Issued By HSBC Software Development (GuangDong) Limited***