Senior AI/ML Engineer — Enterprise Knowledge & Agentic AI

CBRE; United States; On-site; USD 120,000 - 160,000; Full time

Job summary

CBRE Data & Technology seeks a Senior AI/ML Engineer to design, build, and operationalize production-grade AI systems. You will own end-to-end deliverables, from agentic workflows to enterprise knowledge graphs and MLOps pipelines.

You’ll deploy ML models for predictive analytics, optimize RAG pipelines, and collaborate with product teams to deliver AI-driven insights that inform account intelligence and portfolio analytics. Strong Python, DL frameworks, and cloud platforms are essential.

Qualifications

• 5+ years of AI/ML engineering experience with production deployments.
• Track record shipping AI/ML systems in fast-moving environments.
• Experience collaborating with product managers or business stakeholders.
• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related field.

Responsibilities

• Design and implement agentic AI frameworks including multi-agent orchestration, tool-calling pipelines, and autonomous task execution systems.
• Build and optimize RAG pipelines, prompt chaining workflows, and memory systems for enterprise scale.
• Integrate LLM-powered agents with internal APIs, databases, and business systems to automate complex workflows.
• Design and maintain enterprise knowledge graph schemas, entity resolution, and relationship modeling.
• Train, evaluate, and deploy ML models for predictive analytics, classification, and anomaly detection.
• Develop AI-driven insights and summarization capabilities to convert unstructured data into structured BI.

Skills

Python

PyTorch

TensorFlow

HuggingFace

LLM / Generative AI

RAG pipelines

Knowledge Graph

MLOps

Docker

Kubernetes

Cloud AI Platforms

Communication

Education

Bachelor's or Master's in CS/DS/Engineering

Tools

Docker

Kubernetes

Azure ML

SageMaker

Vertex AI

Graph Databases

Job description

CBRE Data & Technology seeks a Senior AI/ML Engineer to design, build, and operationalize production-grade AI systems. You will own end-to-end deliverables, from agentic workflows to enterprise knowledge graphs and MLOps pipelines.

You’ll deploy ML models for predictive analytics, optimize RAG pipelines, and collaborate with product teams to deliver AI-driven insights that inform account intelligence and portfolio analytics. Strong Python, DL frameworks, and cloud platforms are essential.