Principal Cloud & AI Systems Engineer

CBRE; Richardson (TX); On-site; USD 180,000 - 240,000; Full time

Job summary

CBRE is seeking a Principal Systems Engineer to lead Cloud & AI Platform initiatives. You will design and operate data platforms, ML services, and cloud automation across multi-cloud environments, delivering scalable data pipelines and production AI capabilities for CBRE’s cloud engineering and FinOps teams.

The role emphasizes deep technical leadership, end-to-end ML lifecycle, MLOps, and governance, with a focus on cost optimization and efficient cloud operations at enterprise scale.

Qualifications

• Bachelor's degree preferred with 10–15 years of relevant experience.
• In lieu of a degree, a combination of experience and education will be considered.
• Hands-on expertise across data engineering, AI/ML, and cloud-native development.

Responsibilities

• Design, build, and maintain large-scale data pipelines across AWS, Azure, and GCP.
• Architect data lakehouse solutions using Iceberg or Delta Lake.
• Develop distributed data transformation workloads with Spark.
• Build modular data components with governed APIs and lineage tracking.
• Design data quality frameworks with validation, freshness, and schema evolution.
• Investigate and resolve the most complex data pipeline and system issues.

Skills

Data engineering

AI/ML engineering

Cloud-native development

ELT/ETL pipelines

dbt

Apache Spark

Airflow

Python

MLOps

LLMs / Generative AI

Education

Bachelor's degree preferred

Tools

dbt

Apache Airflow

Azure Data Factory

Delta Lake

Apache Iceberg

Spark

MLflow

LangChain

Semantic Kernel

Job description

CBRE is seeking a Principal Systems Engineer to lead Cloud & AI Platform initiatives. You will design and operate data platforms, ML services, and cloud automation across multi-cloud environments, delivering scalable data pipelines and production AI capabilities for CBRE’s cloud engineering and FinOps teams.

The role emphasizes deep technical leadership, end-to-end ML lifecycle, MLOps, and governance, with a focus on cost optimization and efficient cloud operations at enterprise scale.