DevOps / Platform Engineer (Remote, Full-Time) [AS348]

About Smart Working At Smart Working, we believe your job should not only look right on paper but also feel right every day. This isn’t just another remote opportunity - it’s about finding where you truly belong, no matter where you are. From day one, you’re welcomed into a genuine community that values your growth and well-being. Our mission is simple: to break down geographic barriers and connect skilled professionals with outstanding global teams and products for full-time, long-term roles. We help you discover meaningful work with teams that invest in your success, where you’re empowered to grow personally and professionally. Join one of the highest-rated workplaces on Glassdoor and experience what it means to thrive in a truly remote-first world. About the Role As a DevOps / 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, DevOps, 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. Responsibilities - 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 TypeScript 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. Requirements - 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 code and projects, and commitment to improving the wider team. - A trustworthy and accountable approach, demonstrating honesty, attention to detail, early identification of problems and consistent delivery. - Ability to explain technical decisions, implementation approaches and engineering solutions clearly, demonstrating genuine technical understanding. - Ability to work remotely during UK working hours. Nice to Have - Experience with Microsoft Azure, particularly relevant to cloud migration initiatives and Azure Marketplace integration. - Experience working with ClickHouse or other data-intensive platforms. - Experience running Large Language Model (LLM) or AI agent workloads in production. - Scripting experience with Python or Go. - Familiarity with SOC 2, GDPR or other regulated environments.