Senior Solution Engineer
Snowflake
- Location
- US-IL-Chicago-MSO
- Employment
- Full Time
- Work model
- On-Site
- Level
- Senior
- H-1B history
- 110 approvals (FY2023)
- Posted
- 2h ago
Skills
About this role
At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don't just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset— who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are seeking a Chicago-Based Senior Solution Engineer to solve customers' complex problems and drive large deal closures. This role combines technical expertise with business acumen, working directly with sales teams and channel partners to understand customer needs, provide compelling demonstrations, and support enterprise Proof of Concepts. The ideal candidate will be passionate about reinventing the database space — including how AI and ML are transforming it — and comfortable engaging with both executive and technical audiences. IN THIS ROLE AT SNOWFLAKE, YOU WILL: Present Snowflake technology and vision — including our AI and ML platform capabilities — to executives and technical contributors Work hands-on with prospects to demonstrate value throughout the sales cycle, including Cortex AI, Snowpark ML, and agentic workflow use cases Maintain deep understanding of competitive and complementary technologies across data, AI, and ML ecosystems Collaborate with Product Management, Engineering, and Marketing teams Support enterprise Proof of Concepts and implementation designs, including end-to-end ML pipelines and GenAI applications built on Snowflake Design and demonstrate solutions leveraging LLMs, retrieval-augmented generation (RAG), vector search, and AI functions within Snowflake Drive strategic solutions to close business opportunities WE WOULD LOVE TO HEAR FROM YOU IF YOU HAVE: Outstanding presentation skills for both technical and executive audiences Broad experience with Database, Data Warehouse, ETL, and cloud technologies Hands-on expertise with SQL and Python Familiarity with machine learning concepts and frameworks (e.g., scikit-learn, PyTorch, TensorFlow, or similar) Working knowledge of LLMs, generative AI, prompt engineering, and embedding-based search Ability to connect business problems with technical solutions, including AI/ML-driven approaches University degree in computer science, engineering, mathematics, or equivalent experience Strong customer-facing communication skills BONUS POINTS FOR THE FOLLOWING: Experience with Snowflake Cortex AI, Snowpark ML, or Snowflake's Model Registry Experience building data pipelines using open table formats (such as Apache Iceberg or Delta Lake) and managing modern data catalogs (e.g., Unity Catalog, Polaris, Dremio, or AWS Glue Catalog) Familiarity with MLOps practices — model deployment, monitoring, and retraining pipelines Experience building or deploying RAG architectures, agentic workflows, or multi-modal AI applications Exposure to vector databases or semantic