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Apple's Strategic Data Solutions (SDS) team is hiring a hands-on Software Engineering Manager to lead a team of 5-6 engineers based in Cork, Ireland. The team focuses on building analytical solutions and tools that enable fraud prevention, waste reduction, and abuse mitigation across Apple's operations. You will balance direct people management with hands-on technical contribution, working across a global, cross-line-of-business engineering organization.
The Solutions SWE team operates in four core areas: efficiency solutions, internal tooling, operational excellence, and direct line-of-business support. Your responsibilities include directly managing, coaching, and growing the Cork-based engineering team through hiring, performance management, and career development. You will contribute to the functional and technical roadmap in partnership with regional counterparts, gather requirements from fraud investigators, analysts, product managers, and business partners, and own delivery end-to-end from planning through deployment, monitoring, and continuous improvement. You will coordinate across time zones and regional teams to maintain alignment in a distributed organization and partner with the broader SWE organization to align on technical patterns and grow engineering craft.
The role requires hands-on technical leadership: you will write and ship production software alongside your team, with recent code contributions expected. You will work with non-engineering partners to understand requirements and set priorities, and you will ensure the team delivers reliable, scalable production software and automation that reduces manual work across operations, analytics, and engineering.
Qualifications:
- 3+ years leading software engineers, either as a people manager or as a technical lead directing the day-to-day work of a team of at least 3 engineers
- Hands-on experience writing and shipping production software in Python, Java, or a comparable language, with code contributions in the last 2 years
- Experience owning delivery end-to-end, from planning and development through deployment, monitoring, and iteration
- Experience working with non-engineering partners (product, operations, analysts, business stakeholders) to gather requirements and agree on priorities
- Experience working with teams spread across multiple locations or time zones
Preferred Qualifications:
- Experience with or exposure to machine learning, useful for partnering with MLEs
- Track record of quickly getting productive with new AI/LLM tooling
- Hands-on experience with cloud infrastructure and container orchestration (AWS, Kubernetes)
- Experience with data pipeline, warehousing, and/or observability tooling (Airflow, Snowflake, Splunk, Superset)
- Expertise in real-time systems, modern architecture, and data processing at scale
- Experience building systems for fraud prevention or similarly challenging problems
- Educational background in Computer Science or related field, or equivalent practical experience
