AI Senior Principal Engineer

Principal AI Engineer London

About the Role CBRE is building the future of AI-driven data governance and analytics at enterprise scale. We’re looking for a Principal AI Engineer to lead the charge — someone who can architect solutions, ship code, and use AI to move fast.

This is a new, high-impact individual contributor role reporting directly to the Senior Director of Data Governance and Engineering. You’ll have a clear path to building and leading a team as we scale — embedded in a 20-person governance and engineering team, working at the intersection of AI/ML, data quality, and master data management.

Why This Role Matters at CBRE AI is not a future capability at CBRE — it’s the next phase of how we operate at scale. Our data estate spans commercial real estate transactions, property assets, and client relationships across the globe, and the volume and complexity of that data demands intelligence, not just automation. This Principal Engineer will be the first to architect and ship AI-native solutions across our governance and MDM programs — defining how LLMs, agents, and ML models become embedded in how CBRE manages and trusts its data.

Your First Mission (Months 1–6) Build a proof-of-concept using LLMs to automate data stewardship in our Reltio MDM platform — specifically, AI-driven entity matching and merging. Prove that LLMs can make our data cleaner, faster, and smarter.

From there, you’ll help shape how CBRE adopts AI across data governance, analytics, and beyond — moving from proof-of-concept to production, and from one use case to many.

What you will be doing:

AI/ML Solution Architecture

Architect and implement AI/ML solutions that drive data quality, governance, and analytics at scale across CBRE’s enterprise data estate.

Integrate LLMs via our internal Ellis AI platform into data workflows — entity matching, classification, quality scoring, and anomaly detection.

Design agent frameworks and RAG pipelines that connect CBRE’s proprietary data assets to LLM capabilities in a governed, production-ready way.

Evaluate emerging AI capabilities and translate them into prioritised, implementable solutions aligned to CBRE’s governance and data strategy.

Platform Engineering & Delivery

Build production systems using Python, AWS, Snowflake, and Reltio APIs — you architect and you ship.

Use AI to write code — we expect you to move fast with modern AI-assisted development tooling and set the standard for the team.

Embed AI capabilities into existing data pipelines and governance workflows, ensuring solutions are scalable, observable, and maintainable in production.

Collaboration & Stakeholder Engagement

Collaborate cross-functionally with data engineers, governance teams, DQ engineers, and business stakeholders to identify and prioritize AI use cases.

Partner with the Collibra and SODA engineering leads to identify where AI can accelerate metadata enrichment, DQ automation, and stewardship workflows.

Evangelize AI adoption across the data team — teach, mentor, and influence how CBRE thinks about AI and data at every level of the organization.

What You Bring

Must-Haves:

Experience building production data and engineering systems with demonstrable delivery at enterprise scale.

Deep hands-on experience with LLMs — not just using APIs, but architecting solutions: prompting strategies, RAG, fine-tuning, and agent frameworks.

Expert-level Python and modern ML/AI frameworks.

AWS experience — you know how to build, deploy, and scale on cloud infrastructure.

Track record of shipping AI products that solve real business problems — not just prototypes.

Architect + implementer mindset — you design elegant systems and roll up your sleeves to build them.

Nice-to-Haves:

Experience with Master Data Management (MDM) or Reltio specifically.

Snowflake expertise — data modeling, Snowpark, or Cortex ML.

Prior work in commercial real estate or large enterprise data environments.

Familiarity with Collibra or SODA — understanding how AI augments governance and DQ platforms.

Our Stack

AI Platform - internal LLM platform with OpenAI, Gemini, and more, Claude

Cloud - AWS

Data Warehouse - Snowflake

MDM - Reltio

Data Governance - Collibra

DQ Platform - SODA

Integration - SnapLogic

Languages - Python (primary), SQL

Why CBRE? Why Now? Scale: Fortune 500 company with one of the largest commercial real estate data footprints in the world — your AI solutions will affect decisions made on billions of dollars in transactions

Greenfield opportunity: This is a new role — you’ll define how AI gets built, governed, and scaled here. No legacy decisions to unpick Strong foundation: You’re not starting from scratch — Reltio MDM, Snowflake, Collibra, and SODA are all live and integrated, giving your AI solutions real data to work with from day one

Autonomy: Direct report to senior leadership, architect-level influence, and the freedom to experiment and move fast

Growth trajectory: Start as an IC, grow into leading a team as we scale AI adoption across the data platform

How to Apply Upload you CV and a brief summary note about: 1. The most impactful AI/ML system you’ve built — what was the business problem, and how did you ship it to production? 2. Your experience with LLMs — specifically around agent frameworks, RAG, or fine-tuning in an enterprise context 3. Why you want to work on data governance + AI at enterprise scale

Why CBRE When you join CBRE, you become part of the global leader in commercial real estate services and investment that helps businesses and people thrive. We are dynamic problem solvers and forward-thinking professionals who create significant impact. Our collaborative culture is built on our shared values — respect, integrity, service and excellence — and we value the diverse perspectives, backgrounds and skillsets of our people. At CBRE, you have the opportunity to chart your own course and realise your potential. We welcome all applicants.

Applicant AI Use Disclosure We value human interaction to understand each candidate's unique experience, skills and aspirations. We do not use artificial intelligence (AI) tools to make hiring decisions, and we ask that candidates disclose any use of AI in the application and interview process.