Senior Agentic AI Engineer (ID: 4040)

Stafide; Amsterdam; On-site; EUR 120,000 - 180,000; Full time

Job summary

Stafide seeks a Senior Agentic AI Engineer to design, build, and deploy enterprise-grade AI solutions using LLMs, RAG, and multi-agent systems in Amsterdam. You will develop AI-powered automation, intelligent assistants, and data-driven decision platforms, applying LangChain, LlamaIndex, embeddings, and vector databases to deliver production-ready results.

You'll work across Azure and AWS, implement MLOps, ensure security and governance, collaborate with business and engineering teams, and

Qualifications

• 8–10 years of experience in Software Engineering, Data Engineering, or AI Engineering.
• Strong hands-on programming with Python and SQL.
• Hands-on experience with LLMs, Agentic AI, RAG, embeddings, and vector databases.
• Experience with LangChain and/or LlamaIndex.
• Experience with Azure OpenAI or similar AI frameworks and cloud services.
• Knowledge of Databricks and Apache Spark.
• Experience with Airflow for workflow orchestration.
• Strong understanding of cloud platforms such as Azure and/or AWS.
• Experience with Docker and Kubernetes.
• Experience with CI/CD practices and modern software delivery pipelines.
• Understanding of MLOps, including deployment, monitoring, evaluation, and retraining.
• Understanding of AI platform security, governance, scalability, and reliability.

Responsibilities

• Design and develop scalable, production-ready Agentic AI and LLM-based applications.
• Build effective RAG pipelines using embeddings and vector databases.
• Design AI workflows and multi-agent solutions using modern AI frameworks.
• Develop reliable AI and data pipelines using cloud platforms and data engineering technologies.
• Work effectively with Python and SQL to build AI and data-driven solutions.
• Deploy, monitor, evaluate, and continuously improve AI/ML models and applications.
• Apply MLOps practices throughout the AI solution lifecycle.
• Work with containerized workloads using Docker and Kubernetes.
• Implement CI/CD practices for reliable and repeatable AI application delivery.
• Identify and address security, governance, scalability, and reliability considerations in enterprise AI platforms.
• Collaborate effectively with business stakeholders, data teams, software engineers, and other technical teams.
• Translate complex business requirements into practical AI-driven solutions.
• Work independently and take ownership of technical deliverables in a production-focused environment.

Skills

Python

SQL

LLMs

Agentic AI

RAG

Embeddings

Vector databases

LangChain

LlamaIndex

Azure OpenAI

Databricks

Apache Spark

Airflow

Azure/AWS cloud

Docker

Kubernetes

CI/CD

MLOps

Security, governance, reliability

Tools

Docker

Kubernetes

Airflow

CI/CD pipelines

LangChain

LlamaIndex

Job description

As a Senior Agentic AI Engineer, you will:

• Design, build, and deploy enterprise-grade Agentic AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and multi-agent systems.
  
• Develop AI-powered automation, intelligent assistants, and data-driven decision platforms.
  
• Build Agentic AI applications using LLMs, RAG, embeddings, and vector databases.
  
• Design and optimize AI workflows using LangChain, LlamaIndex, and cloud AI services.
  
• Design and implement scalable AI and data pipelines across Azure and AWS environments.
  
• Implement MLOps practices covering model deployment, monitoring, evaluation, and retraining.
  
• Ensure AI solutions are scalable, secure, reliable, governed, and production-ready.
  
• Collaborate with business and engineering teams to translate requirements into AI-driven solutions.
  
• Contribute to the continuous improvement of AI platforms, workflows, and engineering practices.
  

What You Bring to the Table:

• 8–10 years of overall professional experience in Software Engineering, Data Engineering, or AI Engineering.
  
• Strong hands-on programming experience with Python and SQL.
  
• Proven hands-on experience with LLMs, Agentic AI, RAG, embeddings, and vector databases.
  
• Experience with LangChain and/or LlamaIndex.
  
• Experience with Azure OpenAI or similar AI frameworks and cloud AI services.
  
• Knowledge of Databricks and Apache Spark.
  
• Experience with Airflow for workflow and pipeline orchestration.
  
• Strong understanding of cloud platforms such as Microsoft Azure and/or AWS.
  
• Experience with Docker and Kubernetes.
  
• Experience with CI/CD practices and modern software delivery pipelines.
  
• Understanding of MLOps, including model deployment, monitoring, evaluation, and retraining.
  
• Understanding of AI platform security, governance, scalability, and reliability.
  

You should possess the ability to:

• Design and develop scalable, production-ready Agentic AI and LLM-based applications.
  
• Build effective RAG pipelines using embeddings and vector databases.
  
• Design AI workflows and multi-agent solutions using modern AI frameworks.
  
• Develop reliable AI and data pipelines using cloud platforms and data engineering technologies.
  
• Work effectively with Python and SQL to build AI and data-driven solutions.
  
• Deploy, monitor, evaluate, and continuously improve AI/ML models and applications.
  
• Apply MLOps practices throughout the AI solution lifecycle.
  
• Work with containerized workloads using Docker and Kubernetes.
  
• Implement CI/CD practices for reliable and repeatable AI application delivery.
  
• Identify and address security, governance, scalability, and reliability considerations in enterprise AI platforms.
  
• Collaborate effectively with business stakeholders, data teams, software engineers, and other technical teams.
  
• Translate complex business requirements into practical AI-driven solutions.
  
• Work independently and take ownership of technical deliverables in a production-focused environment.
  

What we bring to the table:

• The opportunity to work on enterprise Agentic AI and Generative AI initiatives.
  
• Exposure to cutting-edge technologies including LLMs, RAG, multi-agent systems, embeddings, and vector databases.
  
• Opportunities to work with LangChain, LlamaIndex, Azure OpenAI, Databricks, Spark, and Airflow.
  
• Experience across Azure and AWS cloud environments.
  
• Exposure to modern MLOps, Docker, Kubernetes, and CI/CD practices.
  
• Opportunities to build scalable, secure, and production-ready AI platforms and solutions.
  
• Collaboration with business and engineering teams on AI-powered automation and intelligent decision platforms.
  

Let’s Connect

Want to discuss this opportunity in more detail? Feel free to reach out.