Senior Technical Architect, AI/ML
Designs and deploys customer AI/ML solutions on Snowflake, building data science and MLOps pipelines, proofs of concept, and GenAI capabilities. The role requires 10+ years in customer-facing technical work, cloud architecture expertise, and hands-on experience with SQL, scripting, and ML tools.
About the job
Responsibilities
- Serve as a technical expert on Snowflake for AI/ML workloads.
- Build, deploy, and manage ML pipelines using Snowflake features and ecosystem partner tools based on customer requirements.
- Use SQL, Python, and APIs to build proofs of concept demonstrating implementation techniques and best practices for GenAI and ML workloads.
- Follow best practices and ensure knowledge transfer so customers can extend Snowflake capabilities independently.
- Maintain a deep understanding of competitive and complementary AI/ML technologies and vendors, and position Snowflake appropriately.
- Work with systems integrator consultants at a deep technical level to position and deploy Snowflake in customer environments.
- Guide customers through technical challenges.
- Support Services Delivery team members in developing their expertise.
- Collaborate with Product Management, Engineering, and Marketing to improve Snowflake products and marketing.
- Travel to customer sites approximately 25% of the time.
Requirements
- Minimum 10 years of experience working with customers in a pre-sales or post-sales technical role.
- Ability to present to technical and executive audiences through whiteboarding, presentations, and demos.
- Thorough understanding of the complete data science lifecycle, including feature engineering, model development, model deployment, and model management.
- Strong understanding of MLOps technologies and methodologies for deploying and monitoring models.
- Experience with at least one public cloud platform: AWS, Azure, or Google Cloud.
- Experience with at least one data science tool, such as SageMaker, Azure Machine Learning, Vertex, Dataiku, DataRobot, H2O, or Jupyter Notebooks.
- Experience with large language models, retrieval, and agentic frameworks.
- Hands-on scripting experience with SQL and at least one of Python, R, Java, or Scala.
- Experience with libraries such as Pandas, PyTorch, TensorFlow, or scikit-learn.
- University degree in computer science, engineering, mathematics, or a related field, or equivalent experience.
Nice-to-haves
- Experience with generative AI, large language models, and vector databases.
- Experience with Databricks or Apache Spark, including PySpark.
- Experience implementing data pipelines using ETL tools.
- Experience working in a data science role.
- Proven success with enterprise software.
- Vertical expertise in financial services, retail, manufacturing, or a similar core industry.
Skills
Snowflake, MLOps, AWS, Microsoft Azure, GCP, SQL, Python, R, Java, Scala, pandas, PyTorch, TensorFlow, scikit-learn, LLMs
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