Where data does more
Senior Solutions Architect – AI/ML
Location
North Carolina
Posted
7 days ago
Salary
$160K - $210K / year
Seniority
Senior
Job Description
Senior Solutions Architect – AI/ML
Snowflake
• 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.
Job Requirements
- 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
Benefits
- medical, dental, vision, life, and disability insurance
- 401(k) retirement plan
- flexible spending & health savings account
- at least 12 paid holidays
- paid time off
- parental leave
- employee assistance program
- other company benefits
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