Description
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, ensuring strong governance and quality controls.
- Develop AI-powered accelerators and reusable components that teams can adopt with minimal friction.
- Establish practical guidance for “how we use AI here” for common engineering tasks.
- Data Engineering & Mobile Data Products
- Design, build, and maintain reliable data pipelines and curated datasets using mobile-related data sources.
- Define data models that enable consistent, trusted reporting and AI use cases.
- Implement data quality checks, lineage, monitoring, and documentation.
- Collaborate with security and risk partners to ensure compliant data handling.
- Dashboards & Decision Intelligence (Data-Driven Mobile)
- Build dashboards and decision tools that make excellent use of mobile-related data.
- Create “single pane of glass” views for mobile engineering health.
- Enable proactive management through leading indicators and alerting.
- Partner with mobile leadership to define KPIs that matter.
- AI Evangelism & Engineering Community Enablement
- Evangelise practical AI usage across the engineering community.
- Build a culture of experimentation with discipline.
- Act as a trusted advisor to squads.
- Create internal documentation, FAQs, and troubleshooting guides.
- AI-Native Operating Model Support (Partnering with Mobile CTO)
- Support the Mobile CTO in shaping an AI-native engineering strategy.
- Define lightweight governance that enables innovation while ensuring safe use.
- Establish measurement frameworks to quantify impact.
- 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.
- Strong problem-solving abilities.
- Excellent communication skills.
- Strong experience building production-grade data pipelines and datasets.
- Proven ability to build dashboards/analytics products that drive action.
- Strong understanding of secure data handling and engineering practices.
- Experience working in Agile delivery environments.
Strong Technical Skills (AI/Data Engineering)
- Proficiency in Python and SQL.
- Hands-on experience with AI tooling.
- Experience with analytics and visualisation tools.
- Familiarity with CI/CD and developer toolchains.
- Understanding of experimentation and measurement.