Senior System Integrator for AI Applications

Your role in the team

Our expectations of you

Education

• Completed relevant university degree or equivalent qualification.

Qualifications

• Relevant certifications (e.g., VMware Certified Professional from version 6, ITIL Foundation).

Experience

• Basic knowledge in handling cloud environments and simulation systems (ideally experience with Kubernetes clusters in cloud environments).
• 2 years of experience with Docker, Podman, or similar tools, creating and optimizing portable images (containerization).
• 2 years of experience with CI/CD pipelines (e.g., GitLab, Github Actions, Jenkins, ArgoCD), Test-Driven Development, Monitoring (Prometheus, Grafana, ELK Stack), Infrastructure as Code (e.g., Terraform, Pulumi) (DevOps).
• 2 years of experience in scaling systems horizontally & vertically: auto balancing, CDNs and caching (e.g., Redis), performance analysis (scalability).
• 2 years of experience in using serving frameworks (e.g., vLLM, Triton), autoscaling, load balancing, monitoring, versioning, GPU orchestration, and automated deployment (e.g., Kubeflow, MLFlow) of AI models (MLOps).
• 2 years of experience with using AI models via APIs (local & external), GPU optimization, quantization, and fine-tuning.
• Experience with Prompt/Context Engineering (e.g., LangChain, AutoGen, LangGraph), RAG systems, vector databases (e.g., FAISS, Pinecone).
• Experience with Evaluation & Monitoring of AI systems and Governance (EU AI Act, ISO 42001) (GenAI).