Agentic AI Engineer

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: [email protected]

LinkedIn: https://www.linkedin.com/in/ashakrishnan07/