Role: Senior AI Engineer

Location: Amsterdam, NL

Type: Full-Time/ Permanent

Job Description:

• Proven expertise in Generative AI, Agentic AI, traditional Machine Learning, and automation technologies.
• Deep understanding of:
• Prompt Engineering
• Retrieval-Augmented Generation (RAG) pipelines
• Supervised and Unsupervised Model Tuning
• MLOps/LLMOps pipelines
• AI observability tools and practices
• Hands-on experience designing and deploying enterprise-grade RAG-based solutions using LLMs (e.g., OpenAI, Hugging Face, LLaMA) and vector databases (e.g., Pinecone, Weaviate, FAISS).
• Strong experience in architecting and scaling GenAI-powered chatbots.
• Proficiency in Agentic AI, including practical experience with frameworks such as LangGraph, AutoGen, and CrewAI, and orchestration tooling (e.g., MCP servers) on at least one major hyperscaler platform.
• Solid understanding of Responsible AI principles and ethical AI deployment practices.
• Ability to translate business problems into analytical and AI-driven solutions through strong collaboration with business, data science, and engineering teams.
• Excellent communication, stakeholder management, and consulting skills, with the ability to influence and align cross-functional teams.
• Track record of driving productivity improvements and cost optimization through AI initiatives.

Technical Skills:

• Python with ML/AI libraries (e.g., PyTorch, TensorFlow)
• Prompt Engineering tools and techniques
• GenAI & Agentic AI frameworks (e.g., Langchain, LangSmith, LangFuse)
• Cloud platforms: Azure (AI Foundry), AWS (Bedrock/SageMaker), GCP (Vertex AI)
• MLOps/LLMOps tools: MLflow, Kubeflow, Docker, Kubernetes

Preferred Qualifications

• Experience delivering AI/ML projects within Agile development frameworks
• Hands-on work with Model Feedback Analysis, topic modeling, and sentiment analysis
• Familiarity with AgentOps and OpenTelemetry for monitoring and managing agent-based systems
• Understanding of network security concepts, network telemetry, and analytics