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# Principal Systems Engineer - Cloud & AI Engineering

- **Company:** CBRE Group
- **Location:** Richardson, TX, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Data Analysis, Systems Engineering, Microsoft Azure, Cloud Computing, Cloud Engineering, Continuous Integration, Data Cleansing, Information Engineering, Data Governance, Extract Transform Load (ETL), Database Queries, Python (Programming Language), Machine Learning, OpenAI, Cloud Services, Software Engineering, SQL Databases, Google Cloud, Cloud Platform System, Spring Cloud, Retrieval-Augmented Generation, Large Language Models, Apache Spark, Generative AI, Infrastructure as Code (IaC), Kubernetes, Deployment Automation, Bicep, Machine Learning Operations, Api Design, Google Gemini, Terraform, Data Pipelines, Serverless Computing, Docker
- **Published:** November 1, 2026
- **Apply:** https://www.careercircle.com/jobs/all/all/usa/tx/richardson/4aa32a4e-1a08-4d5a-9a60-56bcbf1367b6

## About the Role

* Bachelor's Degree preferred with 8 years of experience in cloud, software, data, or platform engineering. In lieu of a degree, a combination experience and education will be considered.
 * Proven experience building, deploying, and supporting production AI/ML solutions, including MLOps practices.
 * Hands-on experience delivering Generative AI and LLM solutions with tools such as Azure OpenAI, Bedrock, Gemini, or LangChain.
 * Strong Python skills and experience building APIs and cloud-native applications.
 * Expertise in at least one major cloud platform (Azure, AWS, or GCP), including its data and AI services.
 * Experience building data pipelines (ETL/ELT), with strong SQL skills and familiarity with Spark and lakehouse architectures.
 * Experience with Infrastructure-as-Code, CI/CD, Docker, and Kubernetes.
 * Working knowledge of data governance, security, and observability.
 * Clear communicator who influences technical direction and mentor's others.

## Description

Terraform
Operations
Consulting
Automation
Governance
Innovation
Kubernetes
Data Quality
Azure OpenAI
Google Gemini
Mortgage Loans
Data Pipelines
Microsoft Azure
Decision Making
Data Governance
Software Design
Machine Learning
Data Engineering
Docker (Software)
Anomaly Detection
Project Management
Influencing Skills
Program Management
Technical Standard
Data Preprocessing
Systems Engineering
Amazon Web Services
Facility Management
Property Management
Software Engineering
Predictive Analytics
Investment Management
Cloud-Native Computing
Commercial Real Estate
Artificial Intelligence
Real Estate Investments
Cloud-Native Applications
SQL (Programming Language)
Product Family Engineering
Extract Transform Load (ETL)
Infrastructure as Code (IaC)
Python (Programming Language)
Generative Artificial Intelligence
MLOps (Machine Learning Operations)
Cloud Financial Management (FinOps)
Application Programming Interface (API), As a CBRE Principal Systems Engineer - Cloud & AI Engineering, you will serve as one of the most senior technical individual contributors within Cloud Platform Services. You will lead the design, development, and optimization of enterprise-scale cloud data platforms, AI/ML solutions, and cloud-native services that enable intelligent decision-making, automation, and cost optimization across AWS, Azure, and GCP environments.

This role combines deep expertise in data engineering, artificial intelligence, machine learning, and software engineering to solve complex cloud platform challenges, drive innovation, and establish technical standards across the organization.

This job is part of the Software Engineering job function. They are responsible for successfully executing and monitoring software design requirements and improvements to increase efficiency.

What You'll Do:

 * Design, build, and deploy production AI/ML solutions, including predictive analytics, anomaly detection, and intelligent automation.
 * Build Generative AI and LLM-powered solutions, including RAG architectures, AI assistants, and agentic workflows.
 * Own the machine learning lifecycle from data preparation through deployment, monitoring, and continuous improvement.
 * Build the data pipelines and lakehouse platforms that feed analytics, AI, and FinOps use cases.
 * Modernize cloud platforms across Azure, AWS, and GCP using native data, AI, and engineering services.
 * Develop cloud-native applications, APIs, and automation that extend platform capabilities.
 * Automate deployment and platform operations with Infrastructure-as-Code (Terraform, Bicep) and CI/CD.
 * Support containerized and Kubernetes-based workloads for data and AI solutions.
 * Set standards for data quality, governance, security, and reliability.
 * Partner with cloud engineers, architects, and business stakeholders to shape platform strategy.
 * Mentor engineers, influence technical direction across Cloud Platform Services.
 * Lead by example and model behaviors that are consistent with CBRE RISE values.