Senior Agentic AI Engineer - LLM, MLOps & RAG Expert

koinworx; Netherlands; On-site; EUR 90,000 - 150,000; Full time

Job summary

Koinworx is hiring an experienced Senior Agentic AI Engineer for an onsite opportunity in Amsterdam, Netherlands. The role emphasizes Python, SQL, LLMs, and Agentic AI with hands-on RAG, embeddings, and vector databases. Expertise in LangChain and LlamaIndex, plus Azure OpenAI or similar frameworks is required.

Additionally, experience with Databricks, Spark, Airflow, Docker, Kubernetes, CI/CD, and MLOps is essential for managing deployment and monitoring of AI models.

Qualifications

• 8–10 years of professional experience.
• Strong expertise in Python and SQL.
• Hands-on experience with LLMs and Agentic AI.
• Knowledge of RAG, embeddings, and vector databases.
• Experience with LangChain and LlamaIndex.
• Knowledge of Azure OpenAI or similar AI frameworks.
• Experience with Databricks, Spark, and Airflow.
• Strong understanding of Docker, Kubernetes, and CI/CD.
• Experience in MLOps, model deployment, and monitoring.

Responsibilities

• Develop and work with Agentic AI and LLM-based solutions.
• Apply RAG techniques, embeddings, and vector databases.
• Work with AI development frameworks such as LangChain and LlamaIndex.
• Use Python and SQL for AI and data-related development.
• Work with Databricks, Spark, and Airflow.
• Support model deployment and monitoring activities.
• Work with Docker, Kubernetes, and CI/CD pipelines.
• Apply MLOps practices for AI model management.

Skills

Python

SQL

LLMs

Agentic AI

RAG

embeddings

vector databases

Tools

LangChain

LlamaIndex

Azure OpenAI

Databricks

Spark

Airflow

Docker

Kubernetes

CI/CD

MLOps

Job description

Koinworx is hiring an experienced Senior Agentic AI Engineer for an onsite opportunity in Amsterdam, Netherlands. The role emphasizes Python, SQL, LLMs, and Agentic AI with hands-on RAG, embeddings, and vector databases. Expertise in LangChain and LlamaIndex, plus Azure OpenAI or similar frameworks is required.

Additionally, experience with Databricks, Spark, Airflow, Docker, Kubernetes, CI/CD, and MLOps is essential for managing deployment and monitoring of AI models.