Engineering Manager, Payments (AirCover Insurance Platform)
New
A
AirbnbInsurance technology
Location: Remote - USA; This position is US - Remote Eligible.Full-TimeManager
SalaryPay Range $212,000 — $265,000 USD
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Job Details
- Experience
- 10+ years of relevant experience in the tech industry, including 5+ years as an Engineering Manager owning large-scale software systems.
- Required Skills
- Distributed Systems
Requirements
- Bring 10+ years of relevant experience in the tech industry, including 5+ years as an Engineering Manager owning large-scale software systems.
- Demonstrate a track record of setting and maintaining multi-year technical direction for a live, business-critical platform.
- Have led a major re-architecture or multi-region expansion while continuing to deliver.
- Bring depth in backend platforms, distributed systems, and high-availability services.
- Have strong product judgment exercised through data, including running experiments and using measurement to improve conversion or attach rate.
- Have experience managing and growing senior and staff engineers and enabling them to own initiatives end to end.
- Demonstrate strong communication and influence with technical and non-technical partners, including Legal, Finance, and Operations.
- Show a track record of fostering a culture of Diversity and Belonging within the organization and across the tech community.
- Experience with insurance, payments, fintech, or other regulated domains is a strong plus.
Responsibilities
- Define the long-term technical strategy and architecture for the AirCover insurance platform with senior leaders.
- Set priorities with Product, Data Science, Legal, and Insurance leaders across regional expansion, attach-rate growth, and platform reliability.
- Lead development of reliable, auditable, and scalable systems for policy and coverage management, enrollment, pricing inputs, and experimentation.
- Own the team roadmap, technical direction, and operational health, including incident response and on-call quality.
- Align stakeholders and adjacent teams on shared standards and a common platform approach.
- Work with data scientists and ML engineers to incorporate insights and models into experimentation.
- Stay close to the code through design and code reviews.
- Hire, mentor, and develop engineers and support their career growth.
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