The Role
Design, develop, and deploy enterprise-grade Agentic AI solutions using LLMs, RAG, multi-agent systems, and intelligent automation. Build scalable AI and data pipelines across Azure and AWS, integrate vector databases and enterprise data sources, and implement MLOps for deployment, monitoring, evaluation, and retraining. Collaborate cross-functionally to translate business requirements into reliable production AI applications, applying containerization, orchestration, CI/CD, security, and governance practices.
Summary Generated by Built In
As a Senior Agentic AI Engineer, you will
- Design, develop, and deploy enterprise-grade AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and multi-agent systems.
- Build intelligent AI applications, automation workflows, virtual assistants, and data-driven decision-support solutions.
- Develop and optimize AI workflows using frameworks such as LangChain, LlamaIndex, Azure OpenAI, or similar technologies.
- Implement embedding strategies and integrate vector databases to enable efficient semantic search and knowledge retrieval.
- Design, build, and maintain scalable AI and data pipelines on cloud platforms such as Microsoft Azure and AWS.
- Implement MLOps practices for model deployment, monitoring, evaluation, performance optimization, and retraining.
- Collaborate with business stakeholders, data engineers, software engineers, and other technical teams to deliver AI-driven solutions.
What You Bring to the Table
- 8–10 years of overall experience in Software Engineering, Data Engineering, AI Engineering, or related technical fields.
- Strong programming skills in Python and SQL.
- Hands-on experience developing LLM-based applications and Agentic AI solutions.
- Practical experience with RAG architectures, embeddings, vector databases, and multi-agent systems.
- Experience with LangChain, LlamaIndex, Azure OpenAI, or equivalent AI frameworks and services.
- Knowledge of Databricks, Apache Spark, and Apache Airflow for data processing and orchestration.
- Experience working with cloud platforms, particularly Microsoft Azure and/or AWS.
- Familiarity with MLOps practices, model lifecycle management, and production AI deployments.
- Experience with Docker, Kubernetes, and CI/CD pipelines.
- Understanding of AI security, governance, monitoring, and enterprise-level deployment requirements.
You should possess the ability to
- Design and implement scalable, reliable, and maintainable Agentic AI solutions.
- Develop and optimize LLM workflows to improve response quality, accuracy, and performance.
- Integrate enterprise data sources with AI applications using RAG, embeddings, and vector search.
- Build and manage AI and data pipelines across cloud environments.
- Evaluate AI models and workflows, identify performance issues, and implement improvements.
- Deploy, monitor, troubleshoot, and maintain AI applications in production environments.
- Apply containerization, orchestration, and CI/CD practices to streamline AI solution delivery.
- Work effectively with cross-functional teams and translate business requirements into technical solutions.
What We Bring to the Table
- The opportunity to work on enterprise-scale Generative AI and Agentic AI solutions.
- Exposure to modern AI technologies, LLMs, RAG architectures, and multi-agent systems.
- The opportunity to develop scalable, cloud-based AI applications and intelligent automation solutions.
- A collaborative, Agile working environment focused on innovation and production-ready AI engineering
Let’s Connect
Want to discuss this opportunity in more detail? Feel free to reach out.
Recruiter: Asha Krishnan
Phone: +31 20 369 0609 ; Extn :146
LinkedIn: https://www.linkedin.com/in/ashakrishnan07/
Skills Required
- 8–10 years of experience in software engineering, data engineering, AI engineering, or related technical fields
- Strong programming skills in Python and SQL
- Hands-on experience developing LLM-based applications and Agentic AI solutions
- Experience with RAG architectures, embeddings, vector databases, and multi-agent systems
- Experience with LangChain, LlamaIndex, Azure OpenAI, or equivalent AI frameworks and services
- Knowledge of Databricks, Apache Spark, and Apache Airflow
- Experience with Microsoft Azure and/or AWS
- Familiarity with MLOps, model lifecycle management, and production AI deployments
- Experience with Docker, Kubernetes, and CI/CD pipelines
- Understanding of AI security, governance, monitoring, and enterprise deployment requirements
- Ability to design scalable, reliable, and maintainable Agentic AI solutions
- Ability to collaborate cross-functionally and translate business requirements into technical solutions
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The Company
What We Do
STAFIDE is a Netherlands-based niche technology talent consulting company operating across Europe. It helps organizations identify, recruit, and deploy technology professionals in areas including cybersecurity, cloud engineering, software development, data analytics, ERP, infrastructure, and digital transformation. Its services include recruitment, workforce engagement, secondment, onboarding support, workforce deployment, and workforce analytics that support technology hiring and expansion.
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