Posted 09 July, 2026
AI Engineer - Python
London, United Kingdom
Full Time
Accepting applications until:
31 July 2026
Job Description
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
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:
What You'll Need
31 July 2026
Job Description
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.
