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Powering the agentic revolution in travel. Sabre is an AI-native technology leader, backed by one of the worlds 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. Job Description Manager Software Engineering AI Engineering Excellence The Engineering Manager AI Engineering Excellence 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. Responsibilities AI Engineering Transformation Define and execute the AI engineering adoption strategy across software development teams. Establish AI-first engineering practices that integrate AI throughout requirements analysis, design, coding, testing, documentation, deployment, operations, and support. Drive widespread adoption of approved AI coding assistants, engineering copilots, autonomous agents, and AI-enabled developer platforms. Identify opportunities to automate repetitive engineering, testing, documentation, operational, and support activities using AI. Lead organizational change initiatives that transition teams from traditional software development models to AI-augmented engineering practices. AI Governance, Standards & Engineering Excellence Establish governance frameworks for responsible, secure, and compliant use of AI-generated code and engineering artifacts. Define standards, best practices, quality controls, validation processes, security reviews, and intellectual property safeguards for AI-assisted development. Create reusable engineering playbooks, implementation patterns, and AI adoption guidelines. Ensure adherence to enterprise AI governance, risk management, security, and compliance requirements. Balance innovation and rapid adoption with engineering discipline and operational excellence. Engineering Leadership & People Management Lead, mentor, coach, and develop software engineers, technical leads, and senior engineering talent. Build a culture of innovation, accountability, continuous learning, experimentation, psychological safety, and technical excellence. Drive workforce planning, hiring, onboarding, succession planning, performance management, career development, and talent retention. Establish AI proficiency as a core engineering competency across teams. Coach engineers on prompt engineering, AI-assisted design, AI-powered testing, AI-driven troubleshooting, and effective use of autonomous agents. Build internal AI champions and communities of practice to accelerate organizational capability development. Technical Leadership & Architecture Provide hands-on technical leadership through architecture reviews, design reviews, code reviews, and technology evaluations. Guide teams in integrating Generative AI services, LLM platforms, RAG architectures, agentic workflows, MCP servers, and emerging AI technologies. Promote AI-assisted architecture analysis, code generation, remediation, testing, documentation, and operational support practices. Ensure engineering solutions meet enterprise standards for scalability, performance, reliability, maintainability, observability, and security. Mentor teams in software architecture, distributed systems, cloud-native engineering, object-oriented design, and modern engineering practices. Delivery Excellence & Operational Leadership Own the successful delivery of complex software initiatives across multiple teams. Ensure AI capabilities are effectively .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.