Agentic AI Engineer (ID:4001)
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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+ 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.
Recruiter: Asha Krishnan
Phone: +31 20 369 0609 ; Extn :146
E-mail: asha.k@stafide.nl
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