Senior Solutions Architect
Senior Solutions Architect helping customers design, build, and productionize AI/ML pipelines on Snowflake Data Cloud. Requires 5+ years customer-facing technical experience, deep knowledge of generative AI and ML lifecycles, MLOps, and hands-on Python/SQL skills.
About the job
Responsibilities
- Serve as a technical expert on Snowflake in relation to AI/ML workloads, providing customers with best practices.
- Work with customers to understand AI/ML use cases, discover key requirements, and architect Snowflake-centric solutions.
- Build, deploy, and optimize AI and ML pipelines using Snowflake features and ecosystem partners.
- Hands-on development using SQL, Python, and Cortex AI to build POCs demonstrating implementation techniques and best practices.
- Ensure knowledge transfer to enable customers to extend Snowflake capabilities independently.
- Maintain deep understanding of competitive and complementary AI/ML technologies and position Snowflake effectively.
- Provide guidance on resolving customer-specific technical challenges.
- Support Services Delivery team members in developing expertise.
- Collaborate with Product Management, Engineering, and Marketing to improve Snowflake’s products and marketing.
Requirements
- Minimum 5 years experience working with customers in a pre-sales or post-sales technical role.
- Outstanding presentation skills to technical and executive audiences, including whiteboarding, presentations, and demos.
- Thorough understanding of generative AI and agent lifecycles: document ingestion, vector embedding selection, LLM selection and optimization, genAI monitoring and evaluation.
- Thorough understanding of the complete ML lifecycle: feature engineering, model development, model deployment, and model management.
- Strong understanding of AI/MLOps, including technologies and methodologies for deploying and monitoring models and agents.
- Experience with at least one public cloud platform (AWS, Azure, or GCP).
- Experience with at least one AI/ML platform such as AWS SageMaker, Databricks, GCP Vertex AI, Azure ML, Dataiku, or DataRobot.
- Hands-on scripting experience with SQL and at least one of 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).
Nice-to-Haves
- Experience with Databricks/Apache Spark.
- Experience implementing data pipelines using ETL tools.
- Proven success at enterprise software companies.
- Vertical expertise in FSI, Retail, Manufacturing, or similar.
Skills
Snowflake, AI/ML, Cortex Ai, SQL, Python, AWS, Azure, GCP, SageMaker, Databricks, Vertex Ai, Azure Ml, pandas, PyTorch
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