Job Description

Job Title: AI Engineer / Workflow Automations

Schedule: M-F, 9AM - 6PM Pacific Time

Salary: based on experience

We’re looking for a rare hybrid: part systems architect, part data engineer, part scrappy builder. This is not a theoretical machine learning role—this is hands-on work solving messy, real-world business problems through fast, effective automation.

You’ll collaborate closely with operations and growth teams, turning whiteboard sessions into high-impact automations that drive measurable business outcomes.

To expedite the process, please complete this assessment when submitting your application:

Responsibilities:

• Own end-to-end automation projects from discovery and scoping to deployment and iteration.
• Embed LLMs (OpenAI, Claude, etc.) into real business operations—beyond just demos or prototypes.
• Automate complex workflows using a mix of no-code tools (Zapier, Make/Integromat), code (Python), Google Cloud services, and third-party SaaS APIs.
• Work directly with cross-functional stakeholders (Ops, CX, Finance, Growth) to understand their challenges and build scalable, practical solutions.
• Maintain and improve automation infrastructure across Google Cloud and integrated SaaS platforms.

Requirements:

• Proven experience automating business processes using both no-code platforms and custom-coded solutions.
• Strong working knowledge of LLM APIs and how to integrate them into operational flows (prompt engineering, chaining, etc.).
• Proficiency in Python, Google Cloud (especially Cloud Functions, Pub/Sub, Firestore), and common e-commerce APIs (Shopify, Klaviyo, etc.).
• Strong communicator: able to whiteboard with teams, translate business logic into system logic, and own execution.
• A bias for action—you move quickly, iterate often, and know when to ship v1.
• Experience in e-commerce or direct-to-consumer (DTC) businesses.
• Familiarity with data pipelines and event-driven architecture.
• A portfolio of automations, bots, or internal tools you've built.

Tools to use

• No-Code Tools (Zapier, Make)
• Custom Coding (Python)
• Cloud Services (Google Cloud: Cloud Functions, Pub/Sub, Firestore)
• SaaS APIs (Shopify, Klaviyo)
• Large Language Models (LLMs) (OpenAI, Claude)

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