●Define, own, and continuously evolve the end-to-end architecture for o9’s enterprise platform, ensuring solutions meet enterprise standards for scalability, reliability, security, performance, and cost efficiency when deploying technically-advanced products with a significant amount of deep learning models embedded in them.
●Architect and guide the implementation of scalable, secure data pipelines using modern AI-boosted data engineering technologies, enabling efficient ingestion, processing, and serving of large volumes of structured and unstructured data.
●Lead the productionalization of AI systems by defining and governing MLOps best practices, including model registries, automated training and retraining pipelines, CI/CD for ML, deployment strategies, and continuous monitoring to detect model drift, data drift, and performance degradation.
●Design, train, fine-tune, and deploy deep learning as well as Agentic models, implementing advanced architectures such as Retrieval-Augmented Generation (RAG) and integrating vector database technologies to enable scalable, low-latency, and context-aware AI applications.
●Serve as a principal-level technical leader, mentoring senior and staff engineers, leading architecture and design reviews, and setting engineering standards and patterns that ensure consistency and quality across teams.
●Translate complex business, product, and operational requirements into clear, durable technical architectures, balancing short-term delivery needs with long-term platform evolution.