The role involves designing, developing, and deploying scalable AI, machine learning, and generative AI solutions to address complex business challenges. The engineer will build and operationalize large language model solutions and implement retrieval-augmented generation architectures. Responsibilities include collaborating with data engineers and architects to integrate applications with datasets while ensuring data governance and reliability. The position requires implementing best practices for continuous integration, delivery, and monitoring of models. Additionally, the engineer will optimize model performance to ensure scalability and security across deployed solutions.

Candidates must possess five to eight years of experience in building and deploying AI, machine learning, or generative AI solutions in production environments. Required technical expertise includes proficiency in Python, major machine learning frameworks, and the Azure ecosystem. Applicants are expected to have hands-on experience with retrieval-augmented generation, prompt engineering, and MLOps pipelines. A bachelor’s or master’s degree in computer science, data science, engineering, or a related field is required for this position.