Senior Solution Engineer (AI)

Location: Remote; must be based in North Carolina or South Carolina, United States.

Base salary: $165,000–$216,562 annually. OTE: $220,000–$288,000.

Company

Snowflake provides a governed cloud data platform for data warehousing, data pipelines, machine learning workloads, data sharing, and AI applications.

What you will do

• Present Snowflake’s Data Cloud vision to data engineering leaders, analytics teams, data scientists, executives, prospects, and customers.
• Lead technical discovery of customer data architectures, including pipelines, warehouses, lakehouses, governance gaps, source systems, transformation layers, and consumption patterns.
• Design Snowflake-native reference architectures and guide customers through Data Mesh, Data Lakehouse, real-time streaming, and unified governance patterns.
• Build and deliver tailored demonstrations and proof-of-concepts across data engineering, AI/ML, and data sharing capabilities, including Snowpark, Dynamic Tables, Snowpipe, Cortex AI, the ML model registry, Data Clean Rooms, and Marketplace listings.
• Translate business problems such as churn prediction, supply chain visibility, financial consolidation, and operational analytics into concrete data solutions and quantify their business value.
• Collaborate with sales, channel partners, Product Management, Engineering, and Field teams, feeding customer architecture patterns into the product roadmap.

Requirements

• 3–8 years of industry experience in a pre-sales or solutions architecture role focused on data platforms.
• Deep hands-on expertise with SQL, Python, and cloud data warehouse or data lakehouse architectures, including the ability to write working code during customer sessions.
• Experience with modern data stack technologies: ETL/ELT tools such as dbt, Fivetran, Informatica, and Spark; streaming platforms such as Kafka and Kinesis; orchestration tools such as Airflow and dbt Cloud; BI tools such as Tableau, Looker, and Power BI; and AWS, Azure, or GCP.
• Experience conducting deep data architecture discovery and connecting findings to Snowflake reference architectures.
• Experience positioning AI and ML capabilities in data platforms, including feature stores, model training pipelines, LLM-powered applications, and AI governance.
• Strong understanding of data governance, quality, and compliance challenges including GDPR, CCPA, and PCI.
• Ability to quantify the value of modern data architectures through cost reduction, time-to-insight, pipeline reliability, and data product monetization.
• Demonstrated experience using AI code-generation tools to accelerate prototyping and proof-of-concept delivery.
• University degree in computer science, data science, engineering, mathematics, or a related field, or equivalent practical experience.

Nice to have

• Master’s degree in Data Science or Business Analytics.
• Experience working with GSIs such as EY, Deloitte, Accenture, or Slalom on large data platform programs.

Culture & Benefits

• Customer-obsessed environment focused on rigorous discovery, honest solution assessment, and measurable outcomes.
• Learning culture with direct feedback and professional development support.
• Variable compensation, equity, 401(k), health, dental and vision insurance, flexible PTO, and a professional development budget.
• AI-native, experimental approach to using emerging capabilities and accelerating impact.