Sr Manager Software Engineering

Powering the agentic revolution in travel. Sabre is an AI-native technology leader, backed by one of the world’s largest travel data clouds. Built on an open, modular, cloud-native architecture, Sabre serves as the backbone for both established leaders and bold, new disruptors, guiding them to the next age of travel retailing through intelligent, connected, and personalized experiences. With AI at its core and operating at unparalleled scale, Sabre transforms insights into innovation, empowering airlines, hoteliers, agencies and other partners to retail, distribute and fulfill travel worldwide.

The Sr Engineering Manager is a transformational technology leader responsible for building high-performing engineering teams while driving enterprise-wide adoption of AI-native software engineering practices. This role combines people leadership, technical excellence, delivery accountability, architectural governance, and AI transformation leadership to improve engineering productivity, software quality, developer experience, and business outcomes.

The ideal candidate is a visionary engineering leader who views AI as a foundational engineering capability rather than simply a productivity tool. They possess the ability to influence engineering culture, drive behavioural change through coaching and metrics, and build high-performing teams that embrace continuous improvement. They balance innovation with governance, quality, security, and compliance, while creating an environment where engineers can leverage AI to deliver better software, faster and more effectively.

The successful candidate will establish AI as a core engineering capability across the Software Development Lifecycle (SDLC), leveraging AI-assisted development, autonomous agents, engineering copilots, and modern developer platforms to accelerate delivery while maintaining the highest standards of security, quality, reliability, and compliance.

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Responsibilities

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AI Engineering Transformation

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Define and execute the AI engineering adoption strategy across software development teams.

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Establish AI-first engineering practices that integrate AI throughout requirements analysis, design, coding, testing, documentation, deployment, operations, and support.

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Drive widespread adoption of approved AI coding assistants, engineering copilots, autonomous agents, and AI-enabled developer platforms.

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Identify opportunities to automate repetitive engineering, testing, documentation, operational, and support activities using AI.

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Lead organizational change initiatives that transition teams from traditional software development models to AI-augmented engineering practices.