Senior Data Science Engineer
Sabre Corporation Bengaluru, Karnataka, India
Technology, Information and Internet · 5,001-10,000 employees
About the role
The Senior Data Science Engineer will design and implement GenAI and agentic AI solutions on Google Cloud Platform. They are responsible for building production-grade data pipelines, ensuring system reliability, and mentoring junior team members.
What they look for
Requirements
Candidates must have 5-8 years of experience in software, data, or ML engineering with specific expertise in GCP AI stacks and ADK-based development. Proficiency in Python, Java, and data pipeline technologies like Dataflow and Beam is required.
Full 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 Senior Engineer is hands-on technical expert responsible for designing and implementing data pipeline using dataflow and Beam, GenAI and Agentic AI solutions on Google Cloud Platform using Vertex AI and ADK frameworks. This role focuses on building production-grade systems, ensuring reliability, safety, and cost efficiency, and mentoring junior engineers while contributing to reusable patterns and best practices. The engineer should also develop data pipelines to load into lakehouse.
Key Responsibilities
Solution Design & Development
- Implement GenAI workflows: prompt engineering, RAG pipelines, embeddings, and evaluation.
- Build agentic AI components: planners, tools, memory management, and guardrails using ADK.
- Integrate GCP services: Vertex AI, BigQuery (including vector functions), Cloud Storage, Pub/Sub, Cloud Run, Workflows.
Delivery & Quality
- Write clean, maintainable code with proper documentation and testing.
- Ensure operational readiness: observability, logging, error handling, retries, and rollback mechanisms.
- Optimize performance and cost through caching, batching, and adaptive routing.
Collaboration & Mentorship
- Work closely with Team Lead and Principal Engineer to align on architecture and standards.
- Mentor junior engineers on prompt engineering, agent design, and GCP best practices.
- Participate in code reviews, design discussions, and knowledge-sharing sessions.
Governance & Compliance
- Implement security controls: IAM, VPC-SC, Secret Manager, and data residency requirements.
- Apply Responsible AI principles: safety prompts, content filters, and audit logging.
Required Technical Competencies
- GenAI: Prompt engineering, RAG, embeddings, fine-tuning, evaluation metrics.
- Agentic AI (ADK): Agent loops, tool integration, memory handling, planning strategies.
- GCP Services: Vertex AI, BigQuery, Cloud Storage, Pub/Sub, Cloud Run, Workflows.
- LLMOps: CI/CD pipelines, model registry, telemetry, cost/performance dashboards.
- Security & Compliance: IAM, VPC-SC, DLP, Okta/IAP integration.
- Data pipeline: Dataflow, Apache Beam, Java.
Qualifications
- 5–8 years in software/data/ML engineering; 1–2 years in GenAI/agentic systems.
- Hands-on experience with GCP AI stack and ADK-based agent development.
- Strong coding skills in Python/TypeScript and familiarity with infrastructure-as-code.
- Hands-on experience on Java, Dataflow + Beam or Spark.
- Exposure to LLMOps practices and production deployments.
Outcomes & KPIs
- Delivery: Features shipped on time with minimal defects.
- Quality: Evaluation metrics (faithfulness, grounding) meet thresholds.
- Cost: Demonstrates cost optimization in design and implementation.
- Team Contribution: Active participation in reviews, documentation, and mentoring.
Demonstrated Behaviors (Senior Engineer Level)
Technical Execution
- Delivers high-quality, tested code aligned with architecture standards.
- Proactively identifies performance and reliability improvements.
Collaboration
- Works effectively with team members; shares knowledge openly.
- Communicates risks and blockers early; seeks help when needed.
Responsible AI
- Applies safety and compliance measures consistently.
- Raises concerns about ethical or security risks promptly.
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.
