Principal Systems Engineer - Cloud & AI Engineering

CBRE is hiring a Principal Systems Engineer - Cloud & AI Engineering to lead the design, development, and optimization of enterprise-scale cloud data platforms, AI/ML solutions, and cloud-native services. The role drives technical standards and innovation across cloud environments, enabling intelligent decision-making, automation, and cost optimization.

Responsibilities

• 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

Skills

• 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
• Bachelor's Degree

Benefits

• Opportunity to chart your own course and realize your potential.

Company Overview

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