We’re looking for a talented AI Platform Engineer to help design and build the core infrastructure that powers next-generation AI solutions. This role focuses on creating the scalable, automated, and secure platform that enables rapid experimentation, reliable deployment, and seamless integration of AI technologies across the business. You’ll be part of the team that turns AI ideas into production-ready systems—ensuring every solution operates efficiently, safely, and at scale. Key Responsibilities Deployment and automation Design, build, and maintain CI/CD pipelines for AI workloads using GitOps practices Automate deployments and manage the full release lifecycle for AI and ML models Cloud and infrastructure management Manage containerised environments (Docker, Kubernetes) and optimise cloud resources for scale and cost Develop systems for managing data pipelines, model artefacts, and versioning with proper governance Internal platform enablement Build modular frameworks, SDKs, templates, and self-service tools that empower teams to develop and deploy AI applications independently Establish standards and automation that make AI delivery faster, safer, and more consistent Monitoring, security, and compliance Implement observability and model performance monitoring systems Engineer compliance, security, and governance directly into pipelines, ensuring full auditability and responsible AI practices Cross-platform integration Design and maintain integrations that enable AI systems to work seamlessly across cloud and on-premise environments About You 2–4 years of experience in MLOps, DevOps, or AI infrastructure engineering Strong hands-on experience with AWS, Azure, or GCP , and Docker/Kubernetes Proficient in Python or Bash scripting , with a solid grasp of Infrastructure as Code (Terraform, CloudFormation) Experience implementing GitOps methodologies for version-controlled, auditable environments Skilled in building developer enablement tools such as SDKs, CLIs, or internal templates Knowledge of data governance, security controls , and compliance in production systems Exposure to LLM-based architectures (e.g. RAG, vector databases) and frameworks such as LangGraph, LangSmith, or Langfuse is advantageous Collaborative mindset with strong problem-solving ability and curiosity for emerging AI technologies Why You’ll Love Working Here Flexible leave options including wellbeing, birthday, and volunteer days Hybrid and pet-friendly environment with on-site parking Professional development support including study leave and LinkedIn Learning access Recognition programs, incentive pay, and wellbeing initiatives
