Your Role: AI Engineer – Python
This role sits in the Global:IQ team, building our next-generation intelligence platform. Global:IQ brings together 1st party and partner data, tools and capabilities to turn data into audience understanding and optimised, data-led media plans across audio and out-of-home.
As a mid-level AI Engineer – Python at Global, you will be a core technical contributor, building scalable backend systems that enable our AI and machine learning models to run efficiently and reliably in production.
Key Responsibilities
Backend Engineering (50%): Design, build and maintain robust APIs and microservices using Python, FastAPI and Postgres to power the Global:IQ platform.
Data Engineering (20%): Develop and support data pipelines and integrations that enable Global:IQ’s AI and analytics use cases.
Infrastructure & Data Warehousing (30%): Architect and manage integrations with cloud platforms (AWS) and Snowflake, ensuring data accessibility, reliability and query performance.
What You’ll Love About This Role
Think Big: Help build the “brain” of the company, working on end-to-end AI and data capabilities that directly influence how we plan and deliver media.
Own It: Take features from idea to production, advocating for modern, AI-enabled engineering practices and strong software craftsmanship.
Keep it Simple: Turn complex data and modelling needs into clear, well-structured services and APIs that are easy to understand and maintain.
Better Together: Work in a startup-style, fast-paced environment backed by the data assets, brands and stability of a major media and entertainment company, collaborating with data scientists, engineers and product teams.
What Success Looks Like
In your first few months, you’ll have:
Developed a solid understanding of the Global:IQ architecture, data flows and key use cases.
Delivered your first production services and pipelines at pace, using modern AI-accelerated development practices.
Played a key role in bringing new Global:IQ product features into production for real customers.
Established yourself as a go-to engineer within the team, contributing to best practices and ways of working.
What You’ll Need
Backend Engineering Experience: Around 3+ years’ experience in backend engineering, ideally in product or platform teams.
Python & APIs: Strong proficiency in Python, with hands-on experience using FastAPI (or similar frameworks) and Postgres in production.
Cloud & Data Platforms: Practical experience with cloud platforms and modern data warehouses, ideally including Snowflake.
Data & AI Focus: Exposure to AI or machine learning features and a strong understanding of how to build systems that support data workflows.
Modern Ways of Working: Comfortable using agentic and AI-accelerated engineering tools (e.g. Claude Code, Copilot-style tools) and working in accountable, fast-moving teams.
Outcome Orientation: A passion for using data and intelligence to improve ad campaign efficiency and demonstrate the value of media investment.