Senior Solutions Architect – AI/ML, Services Delivery

This is a fully remote position, open to applicants in North Carolina.

📋 Description

• Serve as a technical authority on all facets of Snowflake concerning AI/ML workloads and offer customers best practice guidance based on Snowflake's technology stack.

• Collaborate with clients to comprehend their AI/ML use cases, identify essential requirements, and design a Snowflake-focused solution for implementation by the Services Delivery team.

• Grasp how to construct and deploy AI and ML pipelines utilizing Snowflake features and/or its ecosystem in accordance with customer needs.

• Engage hands-on when necessary using SQL, Python, and Cortex AI functionalities to create proof of concepts (POCs) that showcase implementation strategies and best practices on Snowflake technology within the AI/ML workload.

• Adhere to best practices, including facilitating knowledge transfer to ensure that customers are fully equipped to expand Snowflake's capabilities independently.

• Maintain a thorough understanding of competitive and complementary technologies and vendors within the AI/ML domain, and how to effectively position Snowflake in comparison.

• Offer advice on resolving specific technical challenges faced by customers.

• Assist other members of the Services Delivery team in enhancing their expertise.

• Work in partnership with Product Management, Engineering, and Marketing to continuously refine Snowflake’s products and promotional strategies.

⛳️ Requirements

• A minimum of 5 years of experience in a pre-sales or post-sales technical position working with customers.

• Exceptional presentation skills for both technical and executive audiences, whether spontaneously on a whiteboard or through formal presentations and demonstrations.

• Comprehensive understanding of common generative AI and agent lifecycles, including document ingestion, vector embedding selection, LLM selection and optimization, as well as genAI monitoring and evaluation methods.

• In-depth knowledge of the complete ML life cycle, encompassing feature engineering, model development, model deployment, and model management.

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

• Familiarity 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 and Vertex AI, AzureML, Dataiku, Datarobot, etc.

• Practical scripting experience with SQL and at least one of the following languages: Python, Java, or Scala.

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

• A university degree in data science, computer science, engineering, mathematics, or related fields, or equivalent experience.

🏝️ Benefits

• Every Snowflake employee is expected to adhere to the company's confidentiality and security standards for managing sensitive data. Compliance with the company’s data security plan is a critical aspect of their responsibilities.