This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Forward Deployment Engineer — Azure AI based in United Kingdom. Join a high-impact engineering role where you will help organizations successfully adopt and operate cutting-edge Azure AI solutions. Acting as the bridge between platform engineering and project teams, you will guide deployments, streamline onboarding, and ensure AI workloads are delivered efficiently and securely. This position combines hands-on cloud engineering with stakeholder collaboration, offering the opportunity to influence platform improvements through real-world implementation feedback. You will work in a modern, remote-first environment alongside experienced engineers, contributing to scalable AI infrastructure while continuously enhancing deployment processes and best practices. If you enjoy solving technical challenges while working closely with customers and engineering teams, this role offers both ownership and meaningful impact. \n Accountabilities Lead the onboarding of projects onto the Azure AI platform by following established deployment frameworks, runbooks, and best practices. Support requestor and client teams throughout onboarding, production launch, and the early operational lifecycle to ensure successful adoption. Configure and adapt Terraform modules, Infrastructure as Code, and CI/CD pipelines to meet project-specific requirements. Deploy and support machine learning workloads while assisting with lifecycle management across Azure environments. Identify deployment challenges, operational bottlenecks, and enhancement opportunities, providing structured feedback to Platform Engineering teams. Continuously improve onboarding documentation, reusable deployment patterns, and technical runbooks while ensuring compliance with security, governance, and operational standards. Requirements 5–8 years of experience in cloud engineering, platform engineering, DevOps, solution engineering, technical consulting, or a related field. Strong hands-on expertise with Microsoft Azure, including the Azure Well-Architected Framework and Azure AI services. Proven experience with Terraform, Infrastructure as Code, and CI/CD tools such as GitHub Actions, Azure DevOps, GitLab CI, or similar platforms. Good understanding of machine learning deployment processes and model lifecycle management. Excellent communication, stakeholder management, and client-facing consulting skills. Professional working proficiency in English. Experience with Azure Machine Learning, Azure AI Foundry, Azure OpenAI, Kubernetes, AKS, containerization, Python automation, LLMs, RAG solutions, or previous customer-facing engineering roles is considered an advantage. Benefits Competitive compensation package. Career growth and continuous learning opportunities. Flexible remote working environment with a high level of ownership. Collaborative, innovative, and engineering-driven culture. Opportunity to contribute to impactful AI and cloud infrastructure projects. International work environment with highly skilled and diverse teams. \n How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1