Senior AWS DevOps and CloudOps Engineer with strong Kubernetes expertise - Tieto Tech Consulting (m/f/d)

A part of global technology organization Tieto, MentorMate creates durable technical solutions that deliver digital transformation at scale by blending strategic insights and thoughtful design with brilliant engineering. With mature and established practices in enterprise web and mobile development, quality engineering, technical architecture, human-centered design, cloud, DevOps, data, and analytics, the company provides its people with the opportunity to work on impactful, global projects for recognizable brands.  

We’re looking to hire a Senior DevOps Engineer with AWS to help modernize and scale a global digital health SaaS platform used for data‑driven and AI-powered healthcare solutions. In this role, you’ll lead the evolution of the cloud, ML, and Kubernetes infrastructure - driving reliability, automation, cost efficiency, and operational excellence across mission‑critical workloads. You’ll work hands‑on with a modern AWS stack (Fargate, EKS, Lambda, S3, RDS), ML platforms (SageMaker, Kubeflow, MLflow), and CI/CD tooling (ArgoCD, GitHub Actions), enabling engineering and data science teams to deliver faster, safer, and at scale. 

Key Responsibilities     

• Lead operations for multi-tenant SaaS workloads on AWS, ensuring scalability, high availability, and cost efficiency 

• Design, implement, and maintain reliable infrastructure for production, data, and AI/ML workloads 

• Own incident response, postmortems, and operational runbooks to improve system reliability and reduce MTTR 

• 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 temas to ensure smooth cross-team delivery  

Required Experience & Qualifications 

• 7+ years of experience in DevOps/ CloudOps/ SRE  

• Solid hands-on experience with AWS (Fargate, EKS, EC2, S3, RDS, Lambda, IAM, CloudWatch, CloudTrail), Kubernetes and containerized workloads 

• Proficiency with CI/CD tools, Infrastructure as Code (IaC), infrastructure automation, and scripting (Python, Bash, or similar) 

• Proven experience with AI/ML platforms (AWS SageMaker, Kubeflow, MLflow, or equivalent), and   cost‑efficient GPU/compute optimization 

• Working knowledge of MongoDB operations, monitoring, and performance tuning 

• Solid understanding of FinOps principles, cloud cost monitoring, and right-sizing strategies 

• Experience with production monitoring & incident management (Splunk, Grafana, OpenTelemetry)  

• Exposure to multi-tenant SaaS architectures and security or compliance frameworks is a plus 

• Strong collaboration, mentoring, and communication skills, with the ability to thrive in a fast-paced, evolving environment 

• Excellent spoken and written English language skills