DevOps​/Platform Engineer; Remote AS348

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As a Dev Ops / Platform Engineer, you will play a key role in supporting and scaling the cloud infrastructure behind an AI-native cybersecurity platform that processes terabytes of data daily. You will take end-to-end ownership of critical infrastructure and contribute to the reliability, scalability and operational efficiency of the platform.

You will join an engineering team of 14+ professionals across Backend, Dev Ops, Endpoint, Frontend and Design, reporting to the VP of Engineering and AI. The team operates with a flat structure and a single-owner model, where engineers independently own their discipline within each project while collaborating closely with others.

This role suits a mid-to-senior engineer who thrives on autonomy, embraces AI-assisted engineering and wants to deliver high-impact solutions.

• Run, maintain and scale production cloud infrastructure supporting a platform that processes terabytes of data daily.
• Own build, deployment and release pipelines for Python, C++ and Type Script applications.
• Build and manage production infrastructure for AI agents, incorporating observability, guardrails and cost controls.
• Take ownership of observability and incident response to maintain platform reliability.
• Automate repetitive operational work using AI agents.
• Take end-to-end ownership of infrastructure and platform engineering projects, from identifying requirements through to delivery.
• Manage multiple priorities, including two major projects alongside smaller AI-driven tasks, while maintaining effective communication and collaboration.

• Deep, hands-on experience managing production cloud infrastructure, with expertise in AWS, Microsoft Azure or Google Cloud Platform (GCP).
• Practical experience with Infrastructure as Code (IaC), using Terraform or equivalent technologies.
• Hands-on experience with Docker and containerised environments.
• Proven ownership of CI/CD pipelines, including build, deployment and release processes.
• Experience implementing and managing observability, incident response and rigorous security practices.
• Daily, hands-on use of AI agents and frontier AI models as part of engineering workflows.
• Demonstrated ability to use LLMs and AI agents autonomously to learn unfamiliar technologies, navigate unfamiliar codebases and manage multiple projects effectively.
• Ability to independently own engineering projects from start to finish rather than simply completing assigned tickets.
• Strong customer focus, including willingness to communicate directly with customers and take ownership of solutions until customer problems are resolved.
• A high sense of urgency, with the judgement to reprioritise work and focus on delivering the greatest impact.
• Ability to set priorities independently, make decisions and deliver results without close supervision while maintaining consistent communication and collaboration.
• A growth mindset, with openness to constructive criticism, willingness to discard or rethink existing…