Senior Software Engineer

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. Job Description Role Summary The Senior Software Engineer is a hands-on technical expert responsible for designing and developing production-grade applications and microservices using Java, Spring Boot, GCP, and Kubernetes , along with Generative AI and Agentic AI solutions using Python, Vertex AI, and ADK . The role involves building rapid AI prototypes and POCs, developing React-based conversational UIs and widgets , and taking solutions through the full lifecycle from design to production deployment. The engineer will focus on scalability, security, reliability, and cost efficiency , while contributing to reusable engineering patterns, best practices, and mentoring junior engineers. Key Responsibilities Software & Full Stack Engineering Design and develop scalable applications using Java/JDK 17+, Spring Boot and microservices . Build REST APIs and integrate with enterprise systems, relational/NoSQL databases and external services. Develop modern web applications and conversational widgets using React and TypeScript/JavaScript . Apply sound software engineering principles, design patterns, automated testing and code quality practices. GenAI & Agentic AI Develop GenAI and Agentic AI POCs using Python, Vertex AI, ADK and related frameworks. Build agentic workflows involving tool calling, planning, memory/context management and guardrails . Implement RAG, embeddings, vector search and prompt engineering solutions. Build integrations using Model Context Protocol (MCP) and other LLM tool/function-calling frameworks. Evaluate emerging AI technologies and transition successful POCs into production-grade solutions. Cloud & Platform Engineering Build and deploy cloud-native applications on Google Cloud Platform (GCP) . Work with GKE/Kubernetes, Docker, Vertex AI, BigQuery, Cloud Storage, Pub/Sub and Secret Manager . Implement CI/CD, monitoring, logging, error handling and production observability. Optimize application and LLM workloads for performance, scalability and cost . Develop data pipelines using Dataflow, Apache Beam or Spark where required. Engineering Leadership & Quality Participate in architecture, design discussions and code reviews. Mentor junior engineers and contribute reusable engineering patterns and best practices. Ensure production readiness through testing, observability, resiliency and operational support. Apply…