Principal Solutions Architect - AI/ML, Services Delivery

AS A PRINCIPAL SOLUTIONS ARCHITECT AT SNOWFLAKE, YOU WILL:

• Be a technical expert on all aspects of Snowflake in relation to the AI/ML workload and provide customers with best practices given Snowflakes technology stack.

• Work with customers to understand their AI/ML use case, discover key requirements, and architect a Snowflake-centric solution to be delivered by Services Delivery.

• Understand how to build, deploy and AI and ML pipelines using Snowflake features and/or Snowflake ecosystem based on customer requirements.

• Work hands-on where needed using SQL, Python, and Cortex AI features to build POCs that demonstrate implementation techniques and best practices on Snowflake technology within the AI/ML workload.

• Follow best practices, including ensuring knowledge transfer so that customers are properly enabled and are able to extend the capabilities of Snowflake on their own

• Maintain deep understanding of competitive and complementary technologies and vendors within the AI/ML space, and how to position Snowflake in relation to them

• Provide guidance on how to resolve customer-specific technical challenges.

• Support other members of the Services Delivery team develop their expertise.

• Collaborate with Product Management, Engineering, and Marketing to continuously improve Snowflake’s products and marketing.

OUR IDEAL SOLUTION ARCHITECT - AI/ML WILL HAVE:

• Minimum 5 years experience working with customers in a pre-sales or post-sales technical role.

• Outstanding skills presenting to both technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos

• Thorough understanding of the common generative AI and agent lifecycles including document ingestion, vector embedding selection, llm selection and optimization, genAI monitoring and evaluation techniques.

• Thorough understanding of the complete ML life-cycle including feature engineering, model development, model deployment and model management.

• Strong understanding of AI/MLOps, coupled with technologies and methodologies for deploying and monitoring models and agents.

• Experience and understanding of at least one public cloud platform (AWS, Azure or GCP)

• Experience with at least one AI/ML platform such as AWS Sagemaker, Databricks, GCP and Vertex AI, AzureML, Dataiku, Datarobot, etc.

• Hands-on scripting experience with SQL and at least one of the following; Python, Java or Scala.

• Experience with libraries such as Pandas, PyTorch, TensorFlow, SciKit-Learn, LangChain/LangGraph, LlamaIndex or similar.

• University degree in data science, computer science, engineering, mathematics or related fields, or equivalent experience

BONUS POINTS FOR HAVING:

• Experience with Databricks/Apache Spark

• Experience implementing data pipelines using ETL tools

• Proven success at enterprise software

• Vertical expertise in a core vertical such as FSI, Retail, Manufacturing etc.