Amdaris
SeniorDevOpsEngineerMoldova(Azure)
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“Senior DevOps Engineer Moldova (Azure) at Amdaris. Skills: DevOps, Azure, AWS, Infrastructure as Code, CI/CD, Observability, Container Orchestration. Own the reliability, scalability, and performance of the platform’s services running on Azure Container Apps and AWS ECS. Build and maintain CI/CD pipelines for automated build, test, and deployment across multiple microservices”
What You'll Achieve.
Own the reliability and operational maturity of a production AI platform; Keeps agentic content workflows running at scale; Ensuring services are observable, deployments are automated, and infrastructure is reproducible; Shape how the team builds, ships, and operates; Focus on the reliability challenges unique to LLM workloads: cost, latency, and non-deterministic failure modes
Industry & Context.
Dual monitor setup and high-spec workstations, Gym allowance, Medical Reimbursement, Full salary covered up to 20 days of sickness, Flexible working hours, Loyalty scheme, Team building activities, special events and conferences, UK/EU Travel opportunities, Snacks and drinks in the office
What They're Looking For.
Must Have
5+ years of DevOps, or platform engineering experience, hands-on experience with Azure (Container Apps, Service Bus, Key Vault, Blob Storage, Azure OpenAI resource management), Infrastructure as code: Terraform, Bicep, or ARM templates, CI/CD pipeline design and maintenance, Docker and container orchestration, Monitoring and observability: New Relic or equivalent, Security practices: secret management, vulnerability scanning, image hardening, Scripting in Python or Bash for automation, Daily user of AI development tools (Cursor, Claude Code, Copilot), Fluent English — spoken and written
Nice to Have
Kubernetes experience as a plus, Experience with LLM observability is a plus, GitHub Actions preferred
What You'll Do.
and performance of the platform’s services running on Azure Container Apps and AWS ECS
Build and maintain CI/CD pipelines for automated build
and deployment across multiple microservices
Implement and manage infrastructure as code across Azure and AWS
Set up and maintain observability — monitoring
Manage Azure Service Bus
and Container Apps configurations
Ensure security best practices — secret management
vulnerability remediation
Implement auto-scaling
and cost optimisation for AI workloads
Support incident response and establish runbooks for production services
Collaborate with AI engineers to optimise LLM API usage
How You'll Work.
Team & Collaboration
Working closely with AI and Full Stack engineers; Collaborate with AI engineers to optimise LLM API usage, token costs, and latency
Communication Scope
Fluent English — spoken and written
Full Job Description
We fuse together exceptional talent who deliver outstanding software solutions. Our approach has helped us grow 60% in 2021, 94% in 2022, while in 2023 we joined forces with Insight, a Fortune 500 company and a leading solutions and systems integrator. With exciting growth plans and cutting-edge projects, there has never been a better time to join our incredible team. About the Role We are looking for an DevOps ready to own the reliability and operational maturity of a production AI platform. You will be the engineering foundation that keeps agentic content workflows running at scale, ensuring services are observable, deployments are automated, and infrastructure is reproducible. Working closely with AI and Full Stack engineers, you will shape how the team builds, ships, and operates, with particular focus on the reliability challenges unique to LLM workloads: cost, latency, and non-deterministic failure modes. This is a role for someone who takes pride in building systems that others depend on. Key Responsibilities: Own the reliability, scalability, and performance of the platform’s services running on Azure Container Apps and AWS ECS. Build and maintain CI/CD pipelines (GitHub Actions) for automated build, test, and deployment across multiple microservices, including Docker image management, registries, and deployment config. Implement and manage infrastructure as code (Terraform, Bicep, or ARM) across Azure and AWS. Set up and maintain observability — monitoring, alerting, logging, and dashboards (New Relic, Langfuse, CloudWatch). Manage Azure Service Bus, Blob Storage, Key Vault, and Container Apps configurations. Ensure security best practices — secret management, image scanning, vulnerability remediation. Implement auto-scaling, load balancing, and cost optimisation for AI workloads. Support incident response and establish runbooks for production services. Collaborate with AI engineers to optimise LLM API usage, token costs, and latency. Required Skills & Qual
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