Salaries · Snowflake
Snowflake Forward Deployed AI Engineer
Snowflake’s FDE-shaped AI roles sit on top of the Data Cloud: Cortex features, governed data access, and customer production paths — not notebook demos.
Comp figures are directional public aggregates. Titles blur across Field Engineering, Forward Deployed AI, and Solutions — confirm coding bar and KPI model in the JD.
Role overview
Expect work around Cortex AI and related Snowflake AI surfaces: retrieval over governed tables, cost/latency budgets, security reviews, and adoption with analysts or operators who already live in the Data Cloud.
Compare with lakehouse peers: Databricks FDE and role framing in FDE vs Solutions Engineer.
Compensation (directional)
| Signal | Cited figure |
|---|---|
| Reported TC range | $180K–$350K |
| Mid discussions | Often mid $200Ks |
| Senior / specialist | Upper band with equity |
Level deep-dives: Mid, Senior.
Technical focus
- SQL / Snowflake warehouses, governance, and cost controls
- Cortex / LLM features with permission-aware data access
- Evaluation, observability, and safe rollout patterns
- Customer change management for AI-assisted workflows
Interview prep
Data systems fluency + customer scoping. Start with the Snowflake FDE interview guide, then practice enterprise system design and case / decomp.
FAQ
Is this the same as a Snowflake Solutions Architect?
Overlap exists. FDE / Forward Deployed AI labels usually imply more hands-on production delivery and outcome ownership after the sale — ask about coding expectations and post-sale vs pre-sales mix.
Related hubs
Jump across salary, interview, and role-comparison pages for the same decision path.