AI Engineer

Description

Job Summary: We are seeking an AI Engineer to design and implement AI and Machine Learning solutions that drive the evolution of the banking business and optimize processes. Key Highlights: 1. Design and implement AI solutions that drive banking business growth. 2. Develop Machine Learning models and Generative AI solutions. 3. Work with cutting-edge technologies such as Azure OpenAI and LLMs. DESCRIPTION We are looking for a passionate **AI Engineer** committed to innovation and digital transformation, capable of designing and implementing Artificial Intelligence solutions that accelerate the evolution of the banking business. You will be responsible for developing Machine Learning models, Generative AI solutions, and LLM-based architectures to optimize processes, enhance customer experience, strengthen risk management, and generate new business opportunities. You will collaborate cross-functionally with business, data, and technology teams to transform strategic challenges into intelligent, scalable, and secure solutions—leveraging technologies such as Azure OpenAI, Machine Learning, RAG, and next-generation cloud platforms. REQUIREMENTS * Bachelor’s degree or higher in Systems Engineering, Computer Science, or related fields. * 3+ years of experience developing AI and Machine Learning solutions. * Proficiency in Python, SQL, and Azure services. * Knowledge of Azure OpenAI, LangChain, and RAG architectures. * Experience in banking or financial environments. * Understanding of risk, fraud, and data governance. * Experience with Docker, Git, and MLOps. ### **What You’ll Do:** * Design, develop, and deploy AI and Machine Learning-based solutions. * Build Generative AI applications using LLMs and RAG architectures. * Develop virtual assistants and intelligent automation tools for customers and employees. * Implement analytical models for fraud detection, customer segmentation, and risk management. * Integrate AI solutions with banking platforms and systems. * Ensure best practices in security, governance, and production model monitoring. * Identify innovation opportunities that improve operational efficiency and customer experience.