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Roles
Tech stack
Required
Location
Menlo Park, CA
Work setup
- Employment
- full-time
- Level
- Mid-level, Senior
- Remote policy
- Onsite (Menlo Park, CA). Customer-facing travel with at least 25% onsite time with strategic customers.
- Remote scope
- onsite
- Travel
- Involve travel, including at least 25% onsite time with strategic customers.
Role details
Responsibilities
- Design, build, deploy, and improve production AI systems on Snowflake
- Work on LLM applications, RAG and agentic workflows
- Create evaluation frameworks and guardrails
- Provide observability and production iteration using Snowpark, Cortex, and Snowflake’s native AI capabilities
- Build and ship customer-facing AI systems end to end
- Lead multi-engineer AI engagements
- Mentor other engineers
- Hands-on architecture and implementation
Requirements
- Strong engineers who can build and ship customer-facing AI systems end to end
- Worked on LLM apps
- Care deeply about evals and quality
- Lead multi-engineer AI engagements
- Mentor other engineers
- Hands-on in architecture and implementation
Application
- Portfolio
- unclear
- GitHub
- unclear
- Cover letter
- unclear
- Apply flow
- ats
Company context
- Product
- Production AI systems on Snowflake, including LLM applications, RAG and agentic workflows
- Industry
- unclear
Description
I’m part of Snowflake’s Applied AI / Forward Deployed Engineering team, and we’re hiring for two roles: Forward Deployed Engineer and Senior Forward Deployed Engineer. We work directly with strategic customers to design, build, deploy, and improve production AI systems on Snowflake. That includes LLM applications, RAG and agentic workflows, evaluation frameworks, guardrails, observability, and production iteration using Snowpark, Cortex, and Snowflake’s native AI capabilities. For the FDE role, we’re looking for strong engineers who can build and ship customer-facing AI systems end to end, especially if you’ve worked on LLM apps and care deeply about evals and quality. For the Senior role, we’re looking for someone who can lead multi-engineer AI engagements, mentor other engineers, and still be hands-on in architecture and implementation. Both roles are customer-facing and involve travel, including at least 25% onsite time with strategic customers. If you like working in ambiguity, building real AI systems instead of demos, and partnering closely with customers to get things into production, these roles are a good fit.
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