At Framestore’s Oscar-winning Technology team, innovation is at the heart of what we do, whether this be developing new techniques, new ideas or creative new ways to tell our clients’ stories. Underpinning all of this is a long tradition of research, technology and development - from engineering our bespoke software solutions to gaining early access to bleeding-edge technology and forging vibrant partnerships with leading academic and scientific institutions.
Framestore combines talent and technology to bring life to everything we create. Driven by creativity and inspired by the future, we set out every day to reframe the possible.
About the Role
This is a new, hands-on role within our team. You’ll play a vital part in building the future of our cloud-first and machine learning strategies, writing the core software and automation that drives them. In this role, you will be actively developing high-availability automation workflows and building resilient big data pipelines that scale compute across the business. You will provide cloud and systems support for developers building complex agentic applications, while driving DevOps best practices to ensure our cloud services are built for the future.
You'll drive the evolution of our cloud infrastructure by designing and implementing automation solutions that scale across the organisation. Your work will span cloud-native practices, machine learning infrastructure, and intelligent systems that keep our environment secure, resilient, and cost-effective.
What you’ll do:
Build highly available automation workflows and orchestrators that enable distributed builds, cross-platform compute scaling, and deployment of AI agents and data-heavy models
Design and implement event-driven automation and self-healing cloud systems that proactively detect, diagnose, and remediate infrastructure anomalies
Architect robust cloud security frameworks, identity management, and automated governance baselines across our global footprint
Design and optimise big data infrastructure for handling large metadata datasets and media assets, whilst identifying opportunities to reduce infrastructure spend without compromising performance