La Fosse
Senior DevOps Engineer (AI Infrastructure) - Data & Insights (Legal) - £90K - Terraform/ Azure
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Job Description: Senior DevOps Engineer
I'm exclusively working with a PE-backed organisation at the forefront of data and intelligence services, looking for a Senior DevOps Engineer to help evolve their Azure cloud platform and drive engineering excellence across the business.
This is a great opportunity for a highly skilled DevOps professional with deep expertise in Microsoft Azure, Infrastructure as Code (IaC), and cloud automation to design, build, and optimise secure, scalable, and resilient cloud solutions. You'll sit at the heart of the technology function, helping shape cloud strategy, championing platform best practices, and empowering software and data engineering teams to deliver innovative products faster, more reliably, and at scale.
What You'll Be Doing
- Defining, versioning, and managing multi-cloud GPU and CPU infrastructure through modular, reusable Terraform
- Enforcing rigorous GitFlow branching strategies, code reviews, and automated deployment practices for all infrastructure changes
- Designing, building, and maintaining secure, high-speed CI/CD pipelines within Azure DevOps to automate code promotion and MLOps workflows
- Leading the response, containment, and resolution of critical platform outages, acting as a primary escalation point for high-priority cloud and infrastructure incidents
- Diagnosing complex, low-latency platform bottlenecks, performance regressions, and cloud-to-cloud networking issues, and implementing permanent structural fixes
- Acting as the direct engineering point of contact for external support teams on active incidents, complex escalations, and day-to-day infrastructure maintenance
- Documenting complex technical architectures clearly and articulating system requirements, post-mortems, and engineering strategy to technical and non-technical stakeholders alike
- Architecting and maintaining highly available MLOps platforms across AWS and Azure environments
- Building self-service infrastructure tools, deployment templates, and continuous training/inference pipelines to eliminate friction for engineering teams
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What They're Looking For
- Demonstrable DevOps experience with a proven focus on building software engineering platforms or AI/ML infrastructure
- Advanced proficiency in Infrastructure as Code, with a track record of building and maintaining complex, automated, version-controlled cloud environments + deep expertise in Terraform and cloud-native provisioning frameworks is essential
- Experience implementing CI/CD-driven infrastructure deployment pipelines
- Production-level experience managing GitFlow workflows and native CI/CD execution inside Azure DevOps
- Proven, production-level expertise managing enterprise-grade infrastructure across both AWS and Azure environments
- Exceptional analytical skills with a track record of troubleshooting complex distributed systems and managing high-pressure production incidents
- Hands-on experience working directly alongside external engineering providers on joint troubleshooting and complex infrastructure handoffs
- Excellent written and verbal communication skills, with a demonstrated ability to write clear documentation and collaborate across engineering teams
- Hands-on experience supporting software delivery and MLOps tooling (e.g. Kubernetes, Kubeflow, MLflow, Triton, Docker, or SageMaker/Azure ML)
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Key Requirements
- Terraform — advanced, production-grade IaC (modular, reusable, version-controlled)
- Azure DevOps — native CI/CD pipeline design + GitFlow workflow enforcement
- AWS + Azure — proven dual-cloud production experience, not just one with the other as a footnote
- Incident management — leading response/resolution for critical outages, primary escalation point
- Third-party coordination — hands-on experience running joint troubleshooting with external support providers
- Communication — clear documentation, post-mortems, translating technical detail for non-technical stakeholders
Nice to Have
- MLOps tooling — Kubernetes, Kubeflow, MLflow, Triton, Docker, SageMaker/Azure ML
It's a great chance to join an encouraging and collaborative environment with a forward-thinking team that views every technical roadblock as an exciting puzzle to solve!
Great office culture, 2 days a week on site in a brand new office in Central London with lots of progression
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