2 months ago
Base Salary
$165k - $217k/yr
Responsibilities
- Serve as the technical expert positioning Snowflake AI and ML features and value to customer technical stakeholders across the Americas.
- Partner with account teams and customer champions to scope and drive proofs of concept to successful technical wins.
- Prepare executive readouts and business value cases demonstrating Snowflake capabilities.
- Collaborate with product and engineering teams to influence AI and ML roadmaps using customer feedback.
- Publish blog posts, conference presentations, notebooks, demos, and other technical collateral.
- Influence, tailor, and maintain Sales Engineering AI and ML assets, including customer presentations, demonstrations, and customer stories.
Requirements
- 5+ years of experience building and deploying machine learning and generative AI solutions in the cloud.
- Familiarity with generative AI techniques including RAG, few-shot learning, prompt engineering, and fine-tuning for enterprise AI use cases.
- Deep knowledge of Python and common machine learning packages such as LangChain, pandas, scikit-learn, and PyTorch.
- Knowledge of data engineering tools and technologies including dbt, Airflow, and Spark.
- Strong presentation skills for technical and executive audiences, including whiteboarding sessions, formal readouts, and demos.
- Bachelor’s degree required; a master’s degree in computer science, engineering, mathematics, or a related field, or equivalent experience, is preferred.
- Working knowledge of LLM ecosystem tools such as LangChain, LlamaIndex, or other open-source packages.
- Experience with large-scale infrastructure-as-a-service platforms such as AWS, Microsoft Azure, or GCP.
- 1+ years of practical Snowflake experience.
- Knowledge of large-scale database technologies such as Snowflake, Netezza, Exadata, Teradata, or Greenplum.
Tech Stack
Categories
Solutions Engineering
About Snowflake
Snowflake builds a cloud-native data platform used by enterprises to store, integrate, share, and analyze data across AWS, Azure, and Google Cloud. Its core products span data warehousing, data lakes, data engineering, and governed data sharing, sold via consumption-based subscriptions. Founded in 2012 and publicly traded on the NYSE (SNOW) following a 2020 IPO, Snowflake supports analytics and data application workloads across industries.