AI/ ML Engineer

Job description

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. Role Summary The AI Engineer is an independent contributor focused on building and testing GenAI and agentic AI components on Google Cloud Platform using Google Enterprise Agent Platform and ADK frameworks. This role emphasizes hands-on coding, learning best practices, and delivering high-quality features under guidance, while developing expertise in GCP and AI workflows. The engineer should be proficient in Java and Python. Key Responsibilities Development & Implementation Implement basic GenAI workflows: prompt engineering, embeddings, RAG pipelines, multi agent workflows. Build and integrate agent tools and simple planners using ADK. Work with GCP services: Google Enterprise Agent Platform, BigQuery, Cloud Storage, Pub/Sub. Quality & Testing Write clean, documented code with unit tests. Participate in code reviews and apply feedback to improve quality. Ensure basic observability: logs, error handling, retries. Collaboration & Learning Work closely with senior engineers and team leads to understand architecture and standards. Attend design discussions, training sessions, and knowledge-sharing forums. Contribute to documentation and team wikis. Compliance & Safety Apply Responsible AI principles: use safety prompts and filters. Follow security guidelines: IAM roles, secret management, and data handling policies. Required Technical Competencies GenAI : Prompt engineering, embeddings, RAG concepts. Agentic AI: Agent loops, tool integration, memory fundamentals. GCP Services: Google Enterprise Agent Platform, BigQuery, Cloud Storage, Pub/Sub. Coding: Proficiency in Python and Java; familiarity with APIs and SDKs. Qualifications 2–4 years in software/data engineering or ML development. Worked on AI/ML projects and cloud platforms (preferably GCP). Strong coding fundamentals. Outcomes & KPIs Delivery: Assigned tasks completed on time with minimal defects. Learning: Demonstrates growth in GenAI and agentic competencies. Collaboration: Actively participates in reviews and team discussions. Demonstrated Behaviors Execution Delivers assigned tasks with attention to detail. Seeks clarity and applies feedback promptly. Learning Shows curiosity; asks questions; adopts best practices. Documents learnings and shares with peers. Collaboration Communicates effectively; works well in team settings. Respects coding standards and security guidelines. We will give careful consideration to your application and review your details against the position criteria. You will receive separate notification as your application progresses. Please note that only candidates who meet the minimum criteria for the role will proceed in the selection process. #LI-Hybrid#LI-GR1