Senior AI Automation engineer-E commerce AI agents

We are building an AI automation company that creates and deploys custom AI agents for e-commerce businesses.

We are looking for a highly skilled AI Automation Engineer who can help us design and build the technical infrastructure behind these systems.

This is NOT a basic chatbot position.

This is NOT a prompt-engineering-only position.
We need someone who can take a business problem, design the technical architecture, build the automation, connect the required platforms, test the system, deploy it, monitor it, and improve it over time.
The ideal candidate is both a developer and a systems thinker.
You should be able to take an idea and turn it into a reliable, scalable AI-powered workflow that can eventually be duplicated and customized across multiple client businesses.
What You Will Help Build

Our first systems will be focused on e-commerce brands.

You will help us build reusable AI infrastructure for areas such as:

1. AI Customer Support Agent

The AI should be able to:

• Answer common customer questions
• Retrieve order information
• Provide shipping and tracking updates
• Assist with returns and exchanges
• Handle product FAQs
• Handle basic order modifications when permitted
• Escalate difficult or sensitive situations to a human
• Log conversations and actions
• Integrate with Shopify and customer support platforms

2. AI Marketing Agent

The marketing system should eventually be capable of helping manage and automate activities across:

• Klaviyo
• Email marketing
• SMS marketing
• Customer segmentation
• Abandoned-cart flows
• Post-purchase flows
• Win-back campaigns
• Promotional campaigns
• Meta / Facebook / Instagram advertising workflows
• TikTok advertising workflows
• Google / YouTube advertising workflows
• Ad copy and creative variations
• Campaign reporting
• Performance monitoring
• Budget and optimization recommendations
• Marketing analytics

Advertising-related systems should operate within clearly defined rules, approvals, budgets, and guardrails.

3. AI Shopping & Conversion Agent

The AI should be capable of:

• Answering product questions
• Recommending products
• Helping shoppers choose the right products
• Creating personalized recommendations
• Upselling and cross-selling
• Recommending bundles
• Addressing common purchase objections
• Helping move customers toward checkout
• Using Shopify product and inventory information

4. AI Cart Recovery & Customer Reactivation Agent

The system should be capable of:

• Identifying abandoned carts
• Triggering personalized follow-up
• Answering customer objections
• Sending approved email /SMS communications
• Recommending products
• Reactivating past customers
• Identifying customers who have not purchased recently
• Triggering win-back campaigns

5. AI Analytics & Growth Agent

The system should eventually pull data from multiple platforms and provide useful business insights such as:

• Revenue
• Conversion rates
• Customer acquisition cost
• ROAS
• Ad performance
• Best-selling products
• Weak-performing products
• Customer-support volume
• Repeat purchase behavior
• Cart abandonment
• Customer retention
• Marketing performance
• Growth opportunities
• Areas where money may be wasted

Core Technical Responsibilities

You will be responsible for helping us:

• Architect AI agent systems from the ground up
• Build workflows using n8n
• Build reusable automation templates
• Connect Shopify through APIs/webhooks
• Integrate Klaviyo
• Integrate customer-support platforms such as Gorgias or Zendesk
• Connect Meta, TikTok and Google marketing systems where APIs permit
• Work with OpenAI, Claude and other LLM APIs
• Build REST and GraphQL API integrations
• Work with webhooks, OAuth, JSON and authentication
• Write custom Python and/or JavaScript when needed
• Build database integrations
• Work with PostgreSQL and/or Supabase
• Build retrieval/knowledge systems where appropriate
• Build reliable logging, monitoring and error handling
• Create human escalation paths
• Develop testing and QA procedures
• Deploy systems into production
• Monitor production systems
• Troubleshoot failed workflows and broken integrations
• Document every system clearly
• Design infrastructure that can be duplicated across multiple client businesses