Lead AI/ML initiatives with over a decade of expertise in Data Warehouse and Business Intelligence technologies. This senior role focuses on architecting and implementing advanced AI/ML solutions, leveraging cutting-edge tools and platforms like Amazon SageMaker, AWS Bedrock, DBT, and Snowflake.

We are seeking a strategic leader to drive innovation and excellence in our AI/ML capabilities, ensuring robust, scalable, and reliable solutions. The ideal candidate will possess a strong technical foundation combined with exceptional leadership and communication skills.

This position offers the opportunity to shape the future of AI/ML within the organization and work with a diverse range of technologies to solve complex business challenges.

Architect and deploy enterprise-scale AI/ML platforms and solutions. Develop and manage MLOps pipelines for efficient model deployment, monitoring, and governance. Collaborate with cross-functional teams including Data Engineering, Data Science, ML Engineering, Cloud, and DevOps. Translate complex business and AI/ML requirements into scalable, reliable technical solutions. Provide technical leadership and mentorship to the AI/ML team. Ensure data governance, security, and privacy standards are met throughout AI/ML development lifecycles. Troubleshoot and resolve complex production issues within AI/ML systems.

A minimum of 10 years of experience in Data Warehouse/BI technologies, with significant exposure to AI/ML solutioning. Proficiency with Amazon SageMaker, AWS Bedrock, DBT, and Snowflake. Experience supporting enterprise-scale AI/ML platforms. Familiarity with data governance, security, privacy, and regulatory requirements. Experience with Generative AI, LLMOps, RAG pipelines, vector databases, or AI agents is highly desirable.

Key competencies include strong analytical and problem-solving abilities, excellent communication and stakeholder management skills, and a keen focus on automation, scalability, and operational excellence.

Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Information Technology, or a related field.