Senior DevOps Engineer (MLOps Focus)
Flatgigs
Posted: April 14, 2026
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Quick Summary
We're looking for a hands-on Senior DevOps Engineer to join our fast-moving engineering team, where you'll play a key role in supporting internal infrastructure and AI workload, focusing on DevOps and security.
Required Skills
Job Description
At AHOY, we reimagine and redefine movement. We’re building a next-generation technology ecosystem across mobility, logistics, and infrastructure, enabling innovators to create, scale, and operate smarter systems.
We’re looking for a hands-on Senior DevOps Engineer to help us build, scale, and secure our multi-cloud infrastructure.
This role sits at the intersection of DevOps, AI infrastructure, and cloud security, where you’ll take ownership of systems powering advanced machine learning workloads. As part of a fast-moving engineering team, you’ll also play a key role in supporting internal IT operations, ensuring reliability across both platform and people.
What You’ll Work on
• Design and maintain secure, scalable cloud infrastructure across Azure and GCP
• Build and optimise CI/CD pipelines and deployment workflows
• Implement and manage Infrastructure as Code (IaC) (Terraform or similar)
• Deploy and operate machine learning pipelines in production environments
• Manage and scale multi-cluster GPU environments for AI workloads
• Set up monitoring, logging, and alerting systems to ensure reliability
• Apply cloud security best practices across infrastructure and access layers
• Troubleshoot and resolve system, deployment, and performance issues
• Provide hands-on IT support (user access, devices, internal systems) to ensure smooth day-to-day operations
• Collaborate with engineering teams to improve scalability, performance, and automation
Requirements:
• 4+ years of experience in DevOps / SRE / Infrastructure Engineering
• Strong experience with Azure and Google Cloud Platform (GCP)
• Hands-on experience building and managing CI/CD pipelines
• Solid expertise in Infrastructure as Code (Terraform, Pulumi, etc.)
• Experience managing Kubernetes environments and GPU workloads
• Proven experience deploying machine learning models or MLOps pipelines
• Strong understanding of cloud security, networking, and system reliability
• Comfortable handling IT support responsibilities alongside core DevOps work
• Strong problem-solving mindset with the ability to work independently