Senior Solutions Architect – AI/ML

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, offering customers best practices aligned with 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 the process of constructing and deploying AI and ML pipelines utilizing Snowflake features and/or its ecosystem based on client specifications.

• Engage hands-on when necessary using SQL, Python, and Cortex AI functionalities to create proofs of concept that illustrate implementation methods and best practices on Snowflake technology within the AI/ML workload.

• Adhere to best practices, including ensuring effective knowledge transfer so that customers are well-equipped to enhance Snowflake's capabilities independently.

• Maintain a thorough understanding of competing and complementary technologies and vendors in the AI/ML domain, along with how to position Snowflake accordingly.

• Offer insights on addressing customer-specific technical challenges.

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

• Partner with Product Management, Engineering, and Marketing to foster continuous improvement of Snowflake’s products and marketing strategies.

⛳️ Requirements

• A minimum of 5 years of experience in a technical role that involves working with customers in pre-sales or post-sales contexts.

• Exceptional presentation skills to both technical and executive audiences, whether through spontaneous whiteboard sessions or formal presentations and demos.

• Comprehensive understanding of common generative AI and agent life cycles, including document ingestion, vector embedding selection, large language model selection and optimization, as well as generative AI monitoring and evaluation techniques.

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

• Strong familiarity with AI/MLOps, including technologies and methodologies for deploying and monitoring models and agents.

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

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

• Proficient in scripting with SQL and at least one of the following programming languages: Python, Java, or Scala.

• Experience with 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

• Medical, dental, vision, life, and disability insurance.

• 401(k) retirement plan.

• Flexible spending and health savings accounts.

• At least 12 paid holidays.

• Paid time off.

• Parental leave.

• Employee assistance program.

• Additional company benefits.