AI Automation Engineer

About the Role

We are hiring an AI Automation Engineer to design and build AI-powered automation systems that eliminate manual work across AIO’s internal departments. This role sits at the intersection of agentic AI, workflow orchestration, and practical software engineering.

The ideal candidate has strong hands-on experience with LLM Agents, Python, LangChain, LangGraph, and n8n, and knows how to deploy these tools to solve real business problems - not just prototype them. You will partner with Operations, Finance, Customer Success, HR, Support, Sales and Marketing and Sales to identify high-impact automation opportunities and ship working solutions fast.

What will be your responsibilities?

• Build LLM-powered agents, including tool use, multi-turn conversations, system prompt engineering, and structured output handling for production automation workflows.
• Design and implement agentic pipelines using LangChain and LangGraph - including stateful multi-agent graphs, conditional routing, human-in-the-loop checkpoints, and agent memory management.
• Build and maintain automation workflows in n8n - connecting internal databases, REST APIs, webhooks, Slack, email, Google Workspace, and AIO product APIs into end-to-end automated processes.
• Embed with internal departments - Operations, Finance, HR, Customer Success, Support, Sales and Marketing - to discover manual workflows, map process pain points, and scope automation opportunities with measurable ROI.
• Build RAG-based internal knowledge tools using vector databases (Pinecone, Weaviate, or pgvector) and the Claude API - enabling departments to query operational data, SOPs, and reports in natural language.
• Write clean, maintainable Python to build custom automation tools, FastAPI microservices, webhook handlers, and data processing scripts that serve as the backbone of automated workflows.
• Harden agents and automation pipelines against failures - including prompt injection, hallucination, API timeouts, and bad outputs - using output validation (Pydantic, JSON schema), guardrails, and fallback handling.
• Optimize automations for token efficiency, API cost, latency, and reliability - applying prompt caching, model routing, batching, and async execution where appropriate.
• Track and report automation impact - time saved, error reduction, and cost savings - maintaining a prioritized backlog and presenting quarterly impact summaries to department leads and AI leadership.
• Document all automation workflows, agent system prompts, tool schemas, n8n flow logic, and API integrations so that every system is maintainable and transferable.

What are we looking for, and what does it require to be the right fit for this role?

• 1–2 years of hands-on experience building AI-powered automation systems, agentic pipelines, or LLM applications that have shipped to real users or internal production.
• Strong Python skills - you write clean, production-ready code, not just notebooks. Comfortable with async Python, Pydantic models, environment management, and packaging.
• Proven, hands-on experience building agents with the Claude and Other LLM APIs - including tool use / function calling, multi-turn system prompts, context window management, and structured JSON output.
• Hands-on with LangChain and LangGraph for building multi-step agent pipelines - chains, tools, memory, and graph-based agent orchestration with state management and conditional branching.
• Practical experience with n8n for building and managing automated workflows - connecting APIs, databases, webhooks, and SaaS tools into triggered, scheduled, or event-driven pipelines.
• Solid understanding of prompt engineering principles - system prompt design, few-shot examples, chain-of-thought structuring, and iterative prompt optimization for consistent agent behavior.
• Experience integrating REST APIs and working with JSON/webhook-based data flows - you can connect, transform, and route data between systems without needing a data engineer.
• Ability to communicate with non-technical stakeholders - translate business problems into scoped automation solutions and clearly explain what is automated, what is monitored, and what requires human review.
• Good documentation habits - every workflow, agent, and integration you build is documented well enough for another engineer to maintain it without you.

Nice to Haves

• Experience with Claude MCP (Model Context Protocol) - building or consuming MCP servers to expose tools and data sources to Claude agents.
• Familiarity with Make (Integromat) or Zapier alongside n8n - able to choose the right orchestration tool for each job and migrate workflows between platforms when needed.
• Exposure to LangSmith, Promptfoo, or similar observability tools for tracing, debugging, and evaluating agent behavior in production.
• Experience with Docker, Redis, Celery, or async task queues for deploying automation services that need to be reliable and observable in production.
• Familiarity with restaurant technology, POS systems, or hospitality SaaS - understanding of how restaurants operate gives you a meaningful head start in this role.
• Prior experience in a startup or high-velocity product environment where you shipped fast, owned your work end-to-end, and iterated based on real usage data.

Why Join AIO?

Our mission is to revolutionize the US restaurant industry by providing a comprehensive and fully integrated solution that empowers restaurant owners to efficiently manage all aspects of their business. Our platform combines our patented AI technology with unparalleled customer support to help owners increase revenue, reduce costs, and improve their overall profit margins.

We believe that restaurants should be able to focus on delivering exceptional dining experiences to their customers, without the added stress of managing complex and disparate systems. That's why we offer an All-In-One super app platform for all their needs, from front-of-the-house operations like ordering, payment, marketing and rewards, to back-of-the-house management like inventory, staff, and financials.

We are laser focused on becoming a significant player in the $55 billion restaurant tech SaaS market. You will be a part of a world class, up-and-coming Silicon Valley funded startup.