S

AI/ML Engineer

SabreBengaluru, Karnataka, IndiaIndia4h ago
onsitefull-timeentry
46 views32 applicants
💼 Competitive Salary

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 Engineer is an early-career contributor focused on building and testing GenAI and agentic AI components on Google Cloud Platform using Vertex AI 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. Key Responsibilities Development & Implementation Implement basic GenAI workflows: prompt engineering, embeddings, and simple RAG pipelines. Build and integrate agent tools and simple planners using ADK. Work with GCP services: Vertex AI, BigQuery, Cloud Storage, Pub/Sub, Cloud Run. 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 Basics: Prompt engineering, embeddings, simple RAG concepts. Agentic AI Basics: Agent loops, tool integration, memory fundamentals. GCP Services: Vertex AI, BigQuery, Cloud Storage, Pub/Sub. Coding: Proficiency in Python; familiarity with APIs and SDKs. Qualifications 0–3 years in software/data engineering or ML development. Exposure to AI/ML concepts and cloud platforms (preferably GCP). Strong coding fundamentals and eagerness to learn GenAI and agentic patterns. 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.

Requirements

  • 0–3 years in software/data engineering or ML development.
  • Exposure to AI/ML concepts and cloud platforms (preferably GCP).
  • Strong coding fundamentals and eagerness to learn GenAI and agentic patterns.
  • 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.

Key Responsibilities

  • Development & Implementation
  • Implement basic GenAI workflows: prompt engineering, embeddings, and simple RAG pipelines.
  • Build and integrate agent tools and simple planners using ADK.
  • Work with GCP services: Vertex AI, BigQuery, Cloud Storage, Pub/Sub, Cloud Run.
  • 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.

About Sabre

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