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Open nowPosted 85 days ago

Senior AI Engineer - Infrastructure & Platform Engineering

Solenix8 open roles

Where
Portugal
Work mode
Hybrid
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Your applicationOpen nowSenior AI Engineer - Infrastructure & Platform EngineeringSolenix · Portugal

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The clock on this job

Early applications get read.

11.8% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.8%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: posted 85 days ago

The posting

Job description

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, 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 a Senior AI Engineer to join a Service Team supporting the operation and evolution of a large-scale, mission-critical computing environment. This is a senior-level role. Candidates are expected to bring at least 5 years of hands-on experience and be able to work autonomously as a Key Person on the contract. You'll work at the intersection of infrastructure engineering and applied AI, helping bring AI-assisted tooling, ML infrastructure, and intelligent automation into a live enterprise environment, alongside broader infrastructure and DevOps responsibilities.

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)
  • Strong understanding of networking concepts and protocols (TCP/IP, DNS, VPN, routing, firewall policies)
  • Knowledge of containerisation technologies (Docker) and Kubernetes orchestration
  • Experience with version control systems and collaborative workflows (e.g. Git)
  • Advanced Linux administration expertise
  • Proficiency in automation/scripting (Bash, PowerShell, or Python)
  • Familiarity with Agile methodologies (Scrum/Kanban) and tools such as Jira
  • Bachelor's degree in a relevant field (or equivalent) plus at least 5 years of relevant professional experience
  • 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

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
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