Senior MLOps/AIOps Engineer

We’re a software house passionate about building solutions that change how our clients use data and artificial intelligence. For over 9 years, we’ve been developing innovative AI-driven products such as InfraSenses and SolarSpy — not just using ready-made tools, but also building machine learning models from scratch.

We’re looking for an experienced MLOps / AIOps Engineer with 7–14 years of experience to join our Client’s team, which is developing cutting-edge Generative AI and Large Language Model solutions for the insurance industry.

In this role, you’ll be responsible for designing, maintaining, and scaling the infrastructure that supports Machine Learning and AI projects — primarily in Azure — using Infrastructure as Code and modern DevOps practices.

You’ll work in an international environment, get access to technologies like Azure AI, Azure ML, and the OpenAI API, and have a real impact on building global AI projects from the ground up. We’re looking for someone who combines strong ML, MLOps, and automation skills and wants to help create practical, large-scale AI solutions.

Key Responsibilities:

• Design, implement, and maintain scalable MLOps pipelines for model training, validation, deployment, and monitoring

• Build and manage cloud infrastructure using Infrastructure as Code tools (Terraform, Pulumi) with a focus on Azure services

• Implement horizontal and vertical scaling solutions using Azure Kubernetes Service (AKS), Container Registry, and App Services

• Design, setup, execute, and debug CI/CD pipelines for ML model deployment and infrastructure provisioning

• Collaborate with data scientists and ML engineers to operationalize machine learning models at scale

• Monitor model performance, data drift, and system health using observability tools and implement automated remediation

• Optimize infrastructure costs while maintaining high availability and performance standards

• Establish and enforce best practices for ML model versioning, experimentation tracking, and reproducibility

• Implement security best practices and compliance requirements across AI/ML infrastructure

• Provide technical guidance and mentorship to junior team members

• Stay current with emerging MLOps tools, platforms, and industry best practices

What We’re Looking For:

• 7–14 years of experience in DevOps, Platform Engineering, or Cloud Infrastructure roles

• Strong expertise with Microsoft Azure, including Azure Machine Learning, AKS, Azure DevOps, and serverless services

• Advanced proficiency in Infrastructure as Code with Terraform and Pulumi

• Proven experience designing and scaling containerized, microservices-based architectures

• Deep understanding of CI/CD pipelines, automation, and quality gates

• Strong scripting skills in Python, Bash, and PowerShell

• Hands-on experience with Docker, Kubernetes, and Helm

• Knowledge of monitoring and observability tools such as Prometheus, Grafana, ELK Stack, and Azure Monitor

Preferred Qualifications

• Familiarity with Machine Learning & AI, including ML lifecycle, TensorFlow/PyTorch, and MLOps tools (MLflow, Kubeflow, Azure ML)

• Strong DevSecOps background — security scanning, compliance, and tools like Twistlock, Aqua Security, Azure Security Center

• Experience with multi-cloud environments (AWS, GCP)

• Knowledge of GitOps workflows (ArgoCD, Flux)

• Understanding of data engineering and big data tools (Spark, Databricks)

• Azure certifications (Solutions Architect, DevOps Engineer Expert) or equivalent

• Familiarity with service mesh technologies (Istio, Linkerd)

Technical Skills

• Cloud Platforms: Azure (primary), AWS, GCP

• Infrastructure as Code: Terraform, Pulumi, ARM templates, Bicep

• Container Technologies: Docker, Kubernetes, AKS, Helm

• CI/CD Tools: Azure DevOps, Jenkins, GitHub Actions, GitLab CI

• Programming Languages: Python, Go, Bash, PowerShell, YAML

• Monitoring & Observability: Prometheus, Grafana, ELK stack, Azure Monitor

• Version Control: Git, GitOps workflows

• Security: DevSecOps practices, vulnerability scanning, compliance frameworks

What We Offer

• The opportunity to work on interesting and innovative projects for a client in the insurance industry

• A chance to grow under the guidance of experienced AI/ML experts

• A training budget to support your technical and professional development

• Private medical care and co-financing of a sports card

• Flexible working hours and the option to work fully remotely