AI Engineer

Responsibilities:

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

Skills:

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