DevOps/Infrastructure Engineer
Summary
Senior Cloud AI Engineer at law firm Freshfields designs and runs secure, scalable AI platforms on Azure — building AKS/container infrastructure, Terraform IaC, CI/CD pipelines, and monitoring/observability — and works with product, data, and engineering teams to take AI solutions to production.
As a Senior Cloud AI Engineer at Freshfields, you will design and operate secure, scalable AI and cloud solutions on Azure. You will build and maintain AI infrastructure, including AKS and containerized workloads, and lead IaC with Terraform. You’ll own CI/CD pipelines, testing, monitoring, and observability to ensure reliable platforms. You will collaborate with product, data, and engineering teams to transition AI solutions to production and drive continuous improvement. This role sits at the intersection of law, technology, and business, contributing to Freshfields’ innovation strategy and partnerships with leading tech providers.
Responsibilities- Design, build, deploy, and support secure, scalable AI and cloud-based solutions on Azure
- Engineer and maintain AI application infrastructure (AKS, containers, cloud-native services)
- Develop and manage Infrastructure as Code (Terraform) for secure environments
- Build and optimize CI/CD pipelines for AI, data, and applications using Azure DevOps
- Implement automated testing, monitoring, alerting, and observability for reliability
- Automate operational processes and environment provisioning with modern DevOps practices
- Collaborate with product, data, and engineering teams to productionize AI solutions
- Monitor platform health, troubleshoot incidents, and drive RCA and improvements
- Ensure solutions are documented, secure, supportable, and aligned with standards
- 5+ years designing and implementing cloud-native solutions, preferably on Azure
- Hands-on Kubernetes (AKS), Docker, and container deployment
- IaC experience with Terraform and automation frameworks
- CI/CD pipelines with Azure DevOps and YAML workflows
- Strong Python programming; shell scripting (PowerShell or Bash); C# or Go a plus
- Experience deploying AI, ML, API, and cloud workloads in production
- Experience operating LLM-based workloads in production (routing, capacity, quotas, rate limiting, streaming, retries, tracing)
- Linux administration, networking, security, and cloud architecture fundamentals
- Enterprise Azure security patterns: private networking, Entra ID, managed identities, RBAC, Key Vault
- Experience with PostgreSQL, Redis, Azure Service Bus, and Azure storage in production
- Git, automated testing frameworks, and modern software engineering practices
- Strong problem-solving and collaboration in Agile environments
- Experience hosting Django or ASGI apps and related streaming workloads on Kubernetes
- excellent communication
- collaboration
- problem-solving
- Azure
- AKS
- Docker