AI Engineer

As an AI Engineer, having Python experience, Prompt Engineering and Generative AI models, and AI use cases application are required. Also, knowledge of AI workflow tools such as LangChain and Google ADK will be a huge plus to help our company improve our business and IT processes with better efficiency, breaking down tasks to use the right learning models, while grounding results via “context engineering” using RAG and MCP protocols to ensure only relevant and good quality results are produced.

You are able to evaluate business challenges, decompose complex problems into AI-enabled workflows, and select the most appropriate models, architectures, and techniques to achieve measurable outcomes. Experience with context engineering, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), agent-based systems, and AI orchestration frameworks is highly desirable. You are expected to design reliable, scalable, and secure AI solutions that deliver accurate, relevant, and high-quality results while aligning with enterprise standards and governance requirements.

Aside from that, you should be able to work independently prioritize and organize your tasks under time and workload pressure. Working in a multinational environment, you can expect cross-region collaboration with teams around the globe, thus being advanced in spoken and written English will be certainly useful.