AI Engineer

Responsibilities:
- Conduct advanced data analysis using Snowflake for business intelligence, ML model development, and enhancement of automation workflows with generative AI.
- Design, train, and evaluate AI models using Azure AIML services, focusing on use cases such as text summarization, anomaly detection, and predictive analytics.
- Develop and enhance OCR and document intelligence models utilizing Azure Document Intelligence, specifically for critical processes such as License Audit and Product Approval.
- Perform rigorous prompt engineering to optimize outputs for the range of generative models in use.
- Execute predictive analytics leveraging Google Cloud AI services, orchestrating workflows using GKE Scheduler and PubSub.
- Communicate findings effectively using data visualization tools (e.g. PowerBI, Tableau) and contribute to the incorporation of data-driven insights into business processes.
- Collaborate closely with product and engineering teams to integrate RAG patterns into core workflows and tools.

Skills:
- Mastery of Snowflake for advanced data analytics, statistical modeling, and ML pipelines.
- Deep understanding and practical experience with Azure AIML services and Google Cloud AIML platforms.
- Advanced knowledge of OCR and document intelligence, with significant experience with Azure Document Intelligence and similar tools.
- Expertise in cloud-based orchestration with GKE Scheduler, Google Pub/Sub, and other similar services.
- Proficiency in statistical analysis, advanced ML model building, and data visualization with relevant tools.
- Strong capabilities in prompt engineering for LLMs and other generative AI models.
- Experience in working with and building RAG pipelines.