DevSecOps Expert in AI

For one of the EU institutions, this role involves participating in an initiative focused on cutting edge technologies to drive innovation and collaboration across networks.

• Master’s degree in IT-related field.
• Expertise in DevOps practices and CI/CD pipeline design.
• Very good knowledge of containerisation and orchestration principles.
• Very good knowledge of AI/ML technologies.
• Ability to follow fast-evolving technologies, especially in the generative AI domain.
• Strong analysis and problem-solving skills.
• Capability to write clear and structured technical documents.
• Good communication skills with both technical and non-technical audiences.
• Ability to give business and technical presentations.
• Ability to participate in and lead technical meetings.

Specific expertise:

• Experience with GitLab and CI/CD pipelines.
• Expertise in Docker and Kubernetes for container orchestration.
• Good knowledge of Data Science and Machine Learning principles and AI frameworks such as Haystack, Langchain.
• Experience with cloud services like AWS or Azure.
• Proficiency in Terraform for Infrastructure as Code.
• Proficiency in programming languages such as Python.
• Experience with development tools like GIT, GitLab, Jira, and Confluence.
• Proficiency in software development best practices with integration of automated security testing throughout the development lifecycle.
• Familiarity with monitoring and observability tools in CI/CD, including structured logging and metrics collection tools like Prometheus and Grafana.
• Familiarity with database management systems such as PostgreSQL and search engines like Elastic Search.

• Design and maintain AI infrastructure for development, training, and inference, including compute, storage, networking, and GPU resources.
• Build and maintain CI/CD and MLOps pipelines for code, data workflows, model training, testing, validation, and deployment.
• Manage containerisation and orchestration using tools such as Docker and Kubernetes.
• Support model operationalisation ensuring reproducibility, versioning, traceability, and controlled releases.
• Implement monitoring, logging, alerting, and performance tracking for infrastructure and AI model endpoints.
• Optimize infrastructure and deployment processes to ensure scalability, reliability, and performance.
• Apply security and compliance controls for infrastructure, access management, secrets handling, and data protection.
• Manage environments and configurations using Infrastructure as Code and configuration management tools.
• Collaborate closely with data scientists, AI engineers, software developers, cybersecurity specialists, and business teams.
• Support governance of data and model lifecycle including versioning, auditability, lineage, backup, and recovery.
• Troubleshoot incidents, deployment issues, and improve automation, resilience, and operational efficiency.