• Lead the design and development of AI and ML applications across cloud or on-prem environments • Build, maintain, and optimize MLOps pipelines for model training, deployment, monitoring, and retraining • Integrate Generative AI models into enterprise applications and workflows • Apply deep learning, neural networks, image processing, or conversational AI where needed • Act as the SME for AI/ML engineering practices, standards, and solution architecture • Collaborate with cross-functional teams to support end-to-end delivery • Ensure production systems meet reliability, scalability, and performance standards • Guide and mentor junior engineers and contribute to technical leadership • Support data engineering pipelines, data preparation, and model operationalization