Senior AWS DevOps Engineer

Tieto

Plovdiv, Bulgaria

We’re looking for a Senior AWS DevOps Engineer to join a global team of our clients, modernizing a cloud-native healthcare SaaS platform used for data-driven and AI-powered solutions. You’ll help shape the infrastructure that enables engineering and data science teams to move faster, deploy safely, and scale confidently. This is a hands-on role for someone who enjoys building reliable systems, improving developer experience, automating everything possible, and working close to both platform and AI/ML teams.

Key Responsibilities

Hands-on work with modern AWS services (Fargate, EKS, Lambda, S3, RDS) and CI/CD tooling such as ArgoCD and GitHub Actions to support reliable, scalable, and production-grade systems
Lead operations for multi-tenant SaaS workloads on AWS, ensuring scalability, high availability, and cost efficiency
Build and maintain scalable infrastructure supporting production applications, data platforms, and AI/ML workloads
Improve operational excellence through incident response, postmortems, automation, and proactive monitoring
Manage and enhance CI/CD pipelines supporting both application and ML deployment workflows
Build and maintain infrastructure automation using Infrastructure as Code (AWS CDK or Terraform)
Enable self-service capabilities for engineering and data science teams
Monitor and optimize cloud usage across compute, GPU, and storage resources, implementing cost controls and forecasting
Support and automate ML pipelines, including training, testing, and deployment using AWS SageMaker, Kubeflow, or MLflow
Manage GPU and compute clusters (EKS, ECS, EC2) for model training and inference workloads
Develop and maintain monitoring, alerting, observability, and security best practices
Collaborate closely with Engineering, Data, AI/ML, and PlatformOps teams to ensure smooth cross-team delivery

Required Experience & Qualifications

6+ years of experience in DevOps/CloudOps/SRE
Strong hands-on experience with AWS services such as EKS, ECS/Fargate, EC2, Lambda, S3, RDS, IAM, CloudWatch, and CloudTrail
Very good understanding of Kubernetes and containerized workloads in production environments
Experience building CI/CD pipelines and automating infrastructure using Infrastructure as Code tools
Proficiency in scripting or automation using Python, Bash, or similar languages
Knowledge of cloud cost optimization, right-sizing strategies, and FinOps best practices
Experience with monitoring and observability platforms such as ELK, Grafana, Splunk and OpenTelemetry
Familiarity with MongoDB operations and performance tuning
Strong communication and collaboration skills in cross-functional environments
Excellent written and spoken English