The ideal candidate has proven experience building AI agents and deploying AI-powered applications in real-world environments, and can help define best practices, architecture, and standards for scalable AI solutions. Key Responsibilities Design and build end-to-end AI use cases across analytics and business workflows Independently query, analyze, and prepare data using platforms such as Databricks or Snowflake (SQL, notebooks, etc.) Integrate and activate AI models (including LLM-based solutions) into business use cases Work within the data infrastructure to ensure correct and consistent data usage for analytics and AI Build AI agents, assistants, and automation solutions on top of enterprise data Connect data, models, and business logic into usable solutions (dashboards, agents, assistants, etc.) Collaborate with IT and data engineering teams for data access and infrastructure alignment (without owning infrastructure) Optimize solutions for performance, scalability, and cost (including compute/token usage) Continuously explore and implement new AI capabilities and tools Qualifications At least 8 years of relevant experience in the field Strong hands-on experience with AI/ML and LLM-based solutions Proven ability to build end-to-end data + AI use cases independently Experience building AI agents or AI-powered applications in production environments Experience with Databricks or Snowflake (SQL, notebooks, or similar development environments) Strong data skills: querying, transformation, and analysis Good understanding of modern data architectures (Lakehouse, cloud environments) Experience integrating AI into real-world applications (automation, assistants, analytics) Experience with cloud platforms (AWS / Azure / GCP) Ability to work independently and drive execution end-to-end
