Growth‑Focused Applied AI Engineer (Production)

Snowplow Analytics Ltd.; United States; Remote; USD 180,000 - 240,000; Full time

Benefits offered by this job

Equity stake

Base Salary

Flexible working

Generous PTO

Medical, Dental & Vision Insurance

401k

Equipment allowance

Enhanced Family leave

Job summary

Snowplow Analytics Ltd. is seeking an Applied AI engineer embedded within Growth to productionize and improve GTM workflows.

You will own the outbound orchestration, campaign tooling, and signals, collaborating with data engineers and platform squads to deliver reliable, scalable solutions. You will build and test AI-enabled workflows, instrument experiments, and ensure fast iteration while maintaining engineering standards and strong data governance.

Qualifications

• Proficient in Python and SQL for production systems.
• Experience building with LLMs and prompts for real tasks.
• Strong API integration and automation tooling (e.g., n8n, Zapier).
• Knowledge of data pipelines into Snowflake and modeling with dbt.

Responsibilities

• Own GTM workflows in production, including outbound orchestration and campaign tooling.
• Review steps before outbound communications and ensure signal validity.
• Own learning loop: instrument sends, run A/B tests, report on messaging impact.
• Maintain signals and enrichment pipelines integrating third-party and first-party data.
• Develop and maintain AI-native workflows embedded in product teams.
• Establish engineering standards: versioning, alerting, runbooks, and handover docs.

Skills

Python

SQL

Git

APIs

n8n

Zapier

LLMs

Prompts

Tools

Snowflake

dbt

Job description

Snowplow Analytics Ltd. is seeking an Applied AI engineer embedded within Growth to productionize and improve GTM workflows.

You will own the outbound orchestration, campaign tooling, and signals, collaborating with data engineers and platform squads to deliver reliable, scalable solutions. You will build and test AI-enabled workflows, instrument experiments, and ensure fast iteration while maintaining engineering standards and strong data governance.