[Hiring] Principal AI Platform Engineer @Snowplow

Role Description

Snowplow is rebuilding how the company runs its own work, and the Applied AI team owns Firn, the single data and AI platform the whole company runs on. Firn already gives people and agents the same governed tools over our Snowflake warehouse through an MCP gateway, routes every model call through one LLM gateway with tracing, runs agentic workflows on a factory framework with a ledger that records every run, and holds the skills catalog the company draws on. Most of the company uses it every day. The platform is at its beginning, and the next stage is to expand it until it holds the company's commercial intelligence and lets agents act on it safely.

You are the principal engineer who leads that expansion. The first engagement is Go-to-Market, full time for about six months. Our buyers research with AI agents now, and reaching them means using our own data and AI to decide which accounts and people to engage, with what, and learning from every experiment. The GTM teams have built a lot:

• Daily account and engagement scoring
• Signal feeds from Apollo, Vector and reo.dev
• An always-on outbound engine
• A paid-media loop
• A curated GTM knowledge base
• The integrations between them

Much of it was built by operational teams to get results fast, and it did. You design how those services come onto Firn, unify and modernize them, build the agents and tools and learning loops on top, and make the whole thing production grade.

This is a principal role. You report to the Senior Director of Applied AI, who still ships code, and work as a peer. Marketing, Sales, Account Management and Partnerships are the platform's customers and set their own priorities. You decide how it gets built and whether it is sound. Once the GTM services run without you, they stay yours as their owner and most of your time goes to what Snowplow needs next.

What you will own

• The GTM intelligence engine on Firn.
• Agents and tools.
• Platform architecture.
• Production grade.
• Logic as code.
• Learning loops.
• Eval and tracing infrastructure.
• The technical bar and the roadmap.

Qualifications

• Years of production software behind you.
• Built LLM systems that real work runs on.
• Platform instincts.
• Data platform fluency.
• Operational discipline.
• Judgment about where an agent belongs.
• An AI-native way of working you can show us.
• Comfort with internal customers who are not engineers.
• Technical direction without a title.

How we hire for this role

The interview process includes a working session where you walk us through how you work with AI on a real task, using your own setup, and a design conversation on a system we run today. We work this way ourselves, and you are welcome to use AI when applying.

Benefits

• Meaningful equity stake
• Competitive Base Salary
• Flexible working
• Generous PTO
• Private Medical Insurance
• Company Pension
• MacBook and home office equipment allowance
• Enhanced Family leave