Senior Solution Engineer (AI/ML)

Location: Remote within the USA, with listed locations including the Bay Area, Denver, Atlanta, Chicago, and New York; approximately 25–30% travel required.

Salary: $165,000–$216,562 annually.

Company

Snowflake provides cloud data, database, data warehouse, analytics, machine learning, and generative AI technologies.

What you will do

• Present Snowflake technology and vision to executive and technical audiences.
• Partner with sales teams and channel partners to understand customer needs and navigate complex sales cycles.
• Build value-based demonstrations and support enterprise proof-of-concept engagements from demo through design and implementation.
• Discover customer architectures and connect business problems with Snowflake data architecture.
• Track competitive and complementary technologies and position Snowflake effectively.
• Collaborate with Product Management, Engineering, and Marketing to improve products and messaging.

Requirements

• 5–7+ years of industry experience, including at least 5 years in pre-sales.
• 5+ years of experience building and deploying machine learning and generative AI solutions in the cloud.
• Strong presentation skills for technical and executive audiences, including whiteboarding, presentations, and demos.
• Hands-on expertise with SQL, SQL analytics, and Python.
• Broad experience with large-scale databases, data warehouses, ETL, analytics, data lakes, data meshes, data fabrics, and cloud technologies.
• Ability to use AI code-generation tools and connect customer business requirements with technical solutions.

Nice to have

• University degree in computer science, engineering, mathematics, or a related field, or equivalent experience.
• Master’s degree in data science or business administration.
• Experience working with global systems integrators such as EY, Deloitte, or Accenture.

Culture & Benefits

• Remote work with regular customer and business travel.
• Customer-obsessed approach focused on making data accessible, usable, and valuable.
• Culture of learning, feedback, experimentation, and challenging conventional thinking.
• Responsibility for maintaining confidentiality and following data security standards.