[Hiring] Applied AI Engineer @Snowplow

Role Description

Snowplow is rebuilding how the company runs its own work, and the Applied AI team owns Firn, the data and AI platform that work runs on, and the engineering standards that go with it. This role is an Applied AI engineer embedded with one business team, the way a site reliability engineer sits inside a product team:

• Your line manager, your code reviewers, and your career path come from Applied AI; your backlog and your day come from the team you serve.
• The Senior Director you report to still ships code.

Your team is Growth, the group inside Marketing that books new meetings for our sellers. Its workflows already produce pipeline:

• An always-on outbound engine that scores accounts daily and sends hundreds of personalized sequences.
• A campaign builder that turns an AE's target list into a reviewed campaign.
• A morning routine that ranks warm contacts by intent signal.
• Enrichment and signal pipelines from Apollo, Vector, Kettlepoint, and reo.dev into Snowflake.
• A paid-media loop that adjusts ads.

Now they need an engineer who makes them production grade and keeps them improving. You take over that estate, make it reliable, and make it better every week. The Director of Growth sets what matters, which is what moves pipeline now. You decide how it gets built and you build it.

You work with:

• Data engineers on scoring models and the semantic layer.
• The platform engineer on the framework your workflows move onto.
• Growth Associates and AEs who use what you ship.

The engineering standards are Applied AI's; the tempo is Growth's.

What you will own

• The GTM workflows in production: the outbound orchestrator and its sequences, the campaign builder, the intent-signal routine, the enrichment and signal pipelines, and the paid-media loop.
• Review steps before anything sends, including agents that check the list, confirm each signal is current, and review the copy before a sequence goes out.
• The learning loop: instrumenting sends, running A/B tests on variants, and showing the Growth team which messaging is working.
• Signals and enrichment: managing pipelines that bring third-party signals and first-party behavior into Snowflake.
• Skills and routines for sellers: Claude skills, campaign tooling, and short working sessions.
• Deliverability and suppression: one set of contact rules, warm-inbox discipline, and suppression windows.
• Engineering standards on your estate: version control, alerting, tracing, runbooks, and documented handover.
• The weekly cadence: a standing backlog with the Director of Growth, priorities set by pipeline, and a short written account of what shipped and what it did.

Qualifications

• Written software that runs in production using Python and SQL.
• Experience with tools like n8n, Clay, or Zapier.
• Built with LLMs for real work, including prompts, tools, structured outputs, and evaluation.
• Experience in alerting, error handling, retries, and recovery.
• Moved data into a warehouse, specifically Snowflake or an equivalent.
• Collaborated with sellers and marketers to understand their needs.
• A fast tempo, measured by meetings booked per week.
• An AI-native way of working demonstrated through a workflow, automation, or agent.
• Comfort being embedded within another team while maintaining engineering standards.

Bonus points for

• Experience with Salesforce, Apollo, Smartlead, Lemlist, or similar GTM tooling and their APIs.
• Experience with email deliverability at volume.
• Experience with paid-media platform APIs.

How we hire for this role

The interview process includes a short technical exercise in code and a working session where you walk us through how you work with AI on a real task, using your own setup. 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
• Medical, Dental & Vision Insurance
• 401k
• MacBook and home office equipment allowance
• Enhanced Family leave