The role involves driving AI strategy from conceptualization through to production within the architecture and engineering group. The engineer will design, build, and iterate on prototypes for Generative and Agentic AI applications. Responsibilities include implementing, training, and fine-tuning machine learning and deep learning models to address complex business problems. The position requires developing and maintaining scalable code for AI systems while managing sophisticated data pipelines. Additionally, the engineer will utilize MLOps practices to deploy applications in containerized environments and monitor their performance. The role also entails researching emerging trends and collaborating with cross-functional teams to translate business requirements into technical solutions.

Candidates must possess strong programming proficiency in Python and deep familiarity with AI-centric libraries. A solid foundation in machine learning algorithms and deep learning architectures is required, alongside hands-on experience with Generative AI, LLMs, and Agentic AI frameworks. Applicants should demonstrate expertise in handling complex datasets and MLOps principles, including containerization and deployment. A Bachelor’s degree or equivalent work experience is required for this position.