SRE Data Intelligence & AI Systems Engineer IV

Sabre Corporation

Dallas (TX)

On-site

USD 130,000 - 170,000

Full time

14 days+
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Benefits offered by this job

Competitive pay & bonuses
Flexible work options
Healthcare coverage
Generous PTO & holidays
Retirement planning support
Family-friendly benefits
Professional development opportunities

Job summary

Sabre Corporation seeks a highly skilled SRE Software Systems Engineer IV to join the Data Intelligence and AI Operations team. You will drive platform reliability, auto-scaling, and cost efficiency across next-generation data platforms, integrating Google Cloud Platform services with ML workloads to power scalable, reliable travel data solutions.

The role requires on-call rotations and after-hours work, with a focus on reducing toil and improving observability across pipelines.

Qualifications

  • Minimum 3 years of experience in systems engineering, DevOps or data engineering in high-volume environments.
  • Strong hands-on experience with Google Cloud Platform, Terraform, BigQuery and Apache Airflow.
  • Proficiency in SQL and Python scripting to automate tasks.
  • Experience with incident response and cross-team collaboration to scale cloud solutions.

Responsibilities

  • Modularize and manage core Google Cloud Platform services using Infrastructure as Code for security and scalability.
  • Optimize resource utilization, auto-scaling policies and cloud spend for large-scale data/ML workloads.
  • Operationalize ML models and Retrieval-Augmented Generation architectures with CI pipelines.
  • Build automated failovers and schema migrations to reduce toil.
  • Enhance pipeline observability and incident response using AI and automation.

Skills

SQL
Python
Incident response
Automation

Tools

Google Cloud Platform
Terraform
BigQuery
Apache Airflow

Job description

Sabre Corporation seeks a highly skilled SRE Software Systems Engineer IV to join the Data Intelligence and AI Operations team. You will drive platform reliability, auto-scaling, and cost efficiency across next-generation data platforms, integrating Google Cloud Platform services with ML workloads to power scalable, reliable travel data solutions.

The role requires on-call rotations and after-hours work, with a focus on reducing toil and improving observability across pipelines.

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