Seeking a Senior Architect with expertise in Data Science, AI/ML, and GenAI to design and implement advanced solutions. This role focuses on leveraging cutting-edge platforms like Snowflake Cortex and Databricks Mosaic AI to build intelligent applications and drive innovation.

This position offers an exciting opportunity to work on end-to-end AI/ML projects, including conversational analytics, AI agents, and LLM-based use cases. You will be instrumental in translating complex business challenges into data-driven AI solutions, ensuring enterprise-grade governance and security throughout the process.

We are looking for a candidate with a strong track record in developing scalable feature engineering pipelines and managing the full model lifecycle with MLOps best practices. Your contributions will directly impact the advancement of our NLP, GenAI, and predictive analytics capabilities.

Design and deploy comprehensive AI/ML and GenAI solutions using Snowflake Cortex and Databricks Mosaic AI. Build intelligent applications incorporating Databricks Genie and Agent Bricks for advanced analytics and AI agents. Develop robust, scalable feature engineering pipelines tailored for modern data platforms. Implement advanced LLM use cases such as RAG, embeddings, and AI assistants. Collaborate with diverse teams to transform business needs into effective AI-driven strategies. Conduct thorough model tuning, evaluation, and lifecycle management adhering to MLOps principles. Ensure robust governance, security, and compliance within all AI pipelines. Champion innovation in NLP, GenAI, and predictive analytics domains.

Requires extensive hands-on experience with Snowflake Cortex, including LLM functions, embeddings, model inference, and AI services. Demonstrates strong expertise in Databricks Mosaic AI, Databricks Genie, and Agent Bricks for building AI solutions. Proven ability to develop and deploy GenAI, LLM, and AI agent-based solutions from concept to production. Possesses strong programming proficiency in Python, PySpark, and core ML frameworks like TensorFlow, PyTorch, and scikit-learn. Experience with Snowflake Snowpark and Databricks Delta Lake for data manipulation and processing. Solid understanding of MLOps, model lifecycle management, and CI/CD pipelines in an enterprise context. Expertise in processing both structured and unstructured data at scale is essential. Strong SQL skills and experience with distributed computing environments are required. Experience integrating AI/ML APIs within broader enterprise systems is crucial.