DevSecOps Expert in AI

For one of the EU institutions we are looking for a DevSecOps Expert in AI. This is a unique opportunity to be part of an exciting initiative in cutting edge technologies that brings about institutional transformation, by driving innovation and collaboration across networks.

Offer:

B2B contract

Remote + 1 trip per month to Luxembourg (negotiable)

Rate: 530-570 EUR/MD

Tasks

Design and maintain AI infrastructure: Set up, configure and manage cloud, on-premises or hybrid environments needed for AI development, training and inference, including compute, storage, networking and GPU resources.

Automate deployment pipelines: Build and maintain CI/CD and MLOps pipelines for code, data workflows, model training, testing, validation and deployment.

Manage containerisation and orchestration: Use tools such as Docker and Kubernetes to package, deploy and scale AI applications and services reliably across environments.

Support model operationalisation: Enable the transition of machine learning models from development to production, ensuring reproducibility, versioning, traceability and controlled releases.

Monitor systems and model services: Implement monitoring, logging, alerting and performance tracking for infrastructure, applications and AI model endpoints, including availability, latency, resource usage and failures.

Ensure reliability, scalability and performance: Optimise infrastructure and deployment processes so AI services can scale efficiently and remain stable under changing workloads.

Implement security and compliance controls: Apply security best practices for infrastructure, access management, secrets handling, software dependencies, data protection and regulatory compliance.

Manage environments and configuration: Standardise development, test and production environments using Infrastructure as Code and configuration management tools to ensure consistency and reproducibility.

Collaborate across teams: Work closely with data scientists, AI engineers, software developers, cybersecurity specialists and business teams to support delivery of AI solutions.

Support data and model lifecycle governance: Contribute to processes for artefact versioning, auditability, lineage, backup, recovery and lifecycle management of datasets and models.

Troubleshoot and improve operations: Investigate incidents, deployment issues and performance bottlenecks, and continuously improve automation, resilience and operational efficiency.

Skills

Master’s degree (IT related)

Expertise in DevOps practices and CI/CD pipeline designVery good knowledge of containerisation and orchestration principles

• Very good knowledge of AI/ML technologies
• Ability to follow the fast pace of emerging technologies and solutions esp. in the gen AI domain
• Strong analysis and problem-solving skills
• Capability to write clear and structured technical documents
• Good communication skills with technical and non-technical audiences
• Ability to give business and technical presentations
• Ability to participate 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, etc.

Experience with cloud services like AWS or Azure, to support data-driven insights with dev-ops practices

Proficiency in using Terraform for IaC Proficiency in programming languages such as Python, along with experience in using development tools like GIT, GitLab, Jira, Confluence, etc.; Proficiency of software development best practices and integration of automated security testing throughout the entire development life cycle

Familiarity monitoring and observability in CI/CD, included structured logging, metrics collection (e.g.: Prometheus, Grafana)

Familiarity with database management systems (PostgreSQL, etc.) and search engines (Elastic Search, etc.)