Forward Deployed Engineer (Finance AI)

TL;DR

Forward Deployed Engineer (Finance AI): Deploying Snowflake's AI platform into production systems for enterprise finance teams with an accent on AI agent workflows, semantic modeling, and finance domain integration. Focus on translating complex financial requirements into shippable AI prototypes and providing field intelligence to product teams.

Location: Hybrid in Menlo Park, CA, USA

Salary: $163,000 – $214,200

Company

Snowflake is powering the era of the agentic enterprise by redefining how work gets done through AI.

What you will do

• Lead end-to-end deployments of Snowflake Finance AI capabilities including Cortex Analyst, Agents, and Search at strategic enterprise accounts.
• Design and build AI agent workflows for repeatable business processes like revenue analysis, cost monitoring, and procurement tracking.
• Develop production finance and analytics dashboards as Streamlit apps deployed natively inside Snowflake.
• Build and improve semantic data models to expose complex schemas to natural language queries for finance executives.
• Translate vague customer requirements into scoped, shippable prototypes and documented playbooks.
• Collaborate with Cortex product and research teams to influence the roadmap based on real-world deployment patterns and gaps.

Requirements

• 3+ years of experience in finance analytics, data engineering, or a technical finance-adjacent role.
• Must be based in or able to work hybrid in Menlo Park, CA.
• Deep finance domain expertise, including ability to analyze balance sheets, ARR, NRR, and FP&A workflows.
• Proficiency in modern, type-hinted Python and advanced SQL (CTEs, window functions).
• Experience using LLM coding assistants (e.g., Cursor, Copilot, Claude) as a primary development environment.
• Ability to write structured prompts and skill files (YAML/Markdown) that behave reliably for non-technical users.

Nice to have

• Hands-on experience with Snowflake Cortex objects and Streamlit.
• Proficiency with Git (PRs, branches, code review).
• Demonstrable experience translating business requirements into technical specifications.

Culture & Benefits

• Direct impact on the evolution of AI products through a tight feedback loop with research teams.
• Experimental mindset focusing on rapid testing of emerging AI capabilities.
• Opportunity to work at the intersection of deep finance expertise and full-stack data AI orchestration.
• High-trust environment where AI is treated as a core collaborator to accelerate impact.