Experience with Snowflake Cortex AI, Snowpark ML, or Snowflake's Model Registry
Experience building data pipelines using open table formats (such as Apache Iceberg or Delta Lake) and managing modern data catalogs (e.g., Unity Catalog, Polaris, Dremio, or AWS Glue Catalog)
Familiarity with MLOps practices — model deployment, monitoring, and retraining pipelines
Experience building or deploying RAG architectures, agentic workflows, or multi-modal AI applications
Exposure to vector databases or semantic search tooling (e.g., Pinecone, Weaviate, pgvector)
Background in a technical presales or solutions engineering role at an AI/ML or data platform company
Outstanding presentation skills for both technical and executive audiences
Broad experience with Database, Data Warehouse, ETL, and cloud technologies
Hands-on expertise with SQL and Python
Familiarity with machine learning concepts and frameworks (e.g., scikit-learn, PyTorch, TensorFlow, or similar)
Working knowledge of LLMs, generative AI, prompt engineering, and embedding-based search
Ability to connect business problems with technical solutions, including AI/ML-driven approaches
University degree in computer science, engineering, mathematics, or equivalent experience
Strong customer-facing communication skills