AI Engineer - Infrastructure & Platform Engineering

AI Engineer - Infrastructure & Platform Engineering

About Solenix and our qualities
Solenix is a privately owned and international company providing engineering and consulting services in the space market, with branches in Germany, Switzerland, Portugal and Italy.
We are known for high-quality services, user-oriented solutions, reliable partnerships and constructive collaboration. Our customers include space agencies such as ESA, EUMETSAT and DLR, as well as large private sector companies.
Solenix is specialized in distributed systems and client applications and applies modern technologies with a focus on high-performing, robust and light solutions.

Why should you apply?

• Solenix is a group of motivated, dynamic and creative people who enjoy high-quality work, as well as a relaxed and flexible work atmosphere.
• You can expect a friendly working environment, exciting and challenging projects and varied team events.
• Solenix focuses on solution-oriented and innovative approaches.

About the Role
We are looking for an AI Engineer to join a Service Team supporting the operation and evolution of a large-scale, mission-critical computing environment. Candidates are expected to bring at least 5 years of hands-on experience in AI or software engineering and be able to work autonomously on the contract. A key part of the role is applying AI and advanced analytics to the customers infrastructure data, such as monitoring metrics and telemetry from the observability stack (e.g. Prometheus, Grafana, CheckMK) and system and application logs (e.g. ELK, Splunk) for anomaly detection, log analysis and predictive monitoring. You will also introduce AI coding assistants and AI-enabled CI/CD tooling into infrastructure-as-code workflows, and support GPU-based AI infrastructure and proofs of concept for emerging AI technologies, alongside broader infrastructure and DecOps responsibilities. Advanced experience across all of these areas is not expected from every candidate; some hands-on AI experience and a willingness to grow towards AI matter more. 

Key Responsibilities

• Support the enablement and evolution of AI/ML infrastructure, including GPU/vGPU-based compute environments and containerised AI workloads
• Apply AI and advanced analytics techniques to infrastructure operations (e.g. anomaly detection, log analysis, predictive monitoring, operational telemetry analysis)
• Contribute to the integration of AI-assisted tools into CI/CD pipelines and infrastructure-as-code workflows
• Support proof-of-concept work, architecture assessments, and technology evaluations for emerging AI/ML capabilities
• Collaborate with infrastructure, DevOps, and platform engineering colleagues as part of a domain-based service team
• Contribute to technical documentation and knowledge-sharing practices

Required Skills & Experience

• Familiarity with AI coding assistants and agentic development tools (e.g. Claude Code, GitHub Copilot, OpenAI Codex, or equivalent)
• Knowledge of containerisation technologies (Docker) and Kubernetes orchestration
• Experience with version control systems and collaborative workflows (e.g. Git)
• Bachelor's degree in a relevant field (or equivalent) plus at least 5 years of relevant professional experience in AI or software engineering)
• Motivation to develop further in the direction of AI (candidates with a software engineering background are welcome)
• Ability to work autonomously and communicate effectively in English (written and verbal)

Desirable Skills

• Experience with machine learning frameworks (PyTorch, TensorFlow, Scikit-learn or equivalent), including model training, evaluation, and deployment
• Experience deploying and operating AI workloads on Kubernetes or cloud platforms, including model inference services
• Experience with AI/ML infrastructure platforms: GPU-based compute environments, distributed training workloads, and optimisation of compute resources for ML pipelines
• Experience leveraging AI-assisted tools integrated with CI/CD platforms (e.g. GitLab AI capabilities)
• Experience with cloud infrastructure architectures (deployment, scaling, lifecycle management)
• Knowledge of ITIL service management processes (incident, change, problem management
• Advanced Linux administration expertise
• Strong understanding of networking concepts and protocols (TCP/IP, DNS, VPN, routing, firewall policies)
• Proficiency in automation/scripting (Bash, PowerShell, or Python)
• Familiarity with Agile methodologies (Scrum/Kanban) and tools such as Jira

What We Offer

• The opportunity to work on a flagship European space/satellite infrastructure programme
• A role combining hands-on AI engineering with real infrastructure impact
• Hybrid work from our UPTEC office in Porto, with occasional travel to Darmstadt, Germany
• Being part of a growing, senior technical team from the ground up