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AI Automation & Workflow Engineer

Seamless Assist
Remote (Global)
RemoteUSD 12 - 13 / hour

About this role

AI Automation & Workflow Engineer

A senior technical hire who builds AI-powered systems from scratch — writing code, connecting APIs, deploying agents, and making sure everything actually works in production.

Field Details

Sector AI Engineering · Automation · Systems Integration · Technical Operations

Level Senior · 3+ years of hands-on technical experience

Education Computer Science degree required (or equivalent technical degree)

Coding Required — Python and/or JavaScript minimum

AI Fluency Advanced — builds with AI APIs, not just uses AI tools

Rate $12–13/hr USD · max TBD

Type Full-time · 40 hrs/week or Part time - 20 hrs/week

Hours Client's business hours — time zone overlap required

Location Remote · Global

What They Do

Build Automation Systems

  • Design and build end-to-end automation workflows using Zapier, Make, or n8n
  • Connect platforms via REST APIs and webhooks — not just drag-and-drop integrations
  • Write scripts (Python or JavaScript) when no-code tools can't do the job
  • Deploy and monitor systems so they keep running without constant attention

AI & Agent Development

  • Build AI agents using OpenAI API, Claude API (Anthropic), or similar LLM APIs
  • Design agent logic — memory, decision trees, tool use, and context management
  • Integrate AI into real business workflows: lead qualification, content generation, support, reporting
  • Use RAG (retrieval-augmented generation) or memory layers when the agent needs to remember
  • things

Systems & Integrations

  • Connect CRMs, databases, communication tools, and custom platforms via API
  • Work with tools like Airtable, HubSpot, GoHighLevel, and similar platforms at the API level
  • Handle data flow, error handling, and edge cases — not just the happy path
  • Manage version control via GitHub and keep code clean and documented

Documentation & Handover

  • Write clear SOPs and technical guides that non-technical people can actually follow
  • Train client teams to use and maintain what was built
  • Make sure nothing is a black box — every system has documentation

AI Tools in Daily Work

  • LLM APIs: OpenAI (GPT-4o), Anthropic (Claude), Mistral, Gemini — for building agents and AI features
  • Automation: n8n, Zapier, Make — with custom code steps and API connections
  • Vector databases: Pinecone, Weaviate, Chroma — for RAG and memory systems
  • Dev tools: GitHub, VS Code, Postman — for building, testing, and version control
  • Cloud: AWS Lambda, Google Cloud Functions, or similar — for deploying lightweight agents
  • AI coding assistants: GitHub Copilot, Cursor, Claude for coding — to build faster
  • Data: Airtable, Google Sheets API, SQL basics — for managing structured data
  • Monitoring: simple logging, error alerts, uptime checks to keep systems healthy

Requirements

  • Computer Science degree or equivalent technical degree — required

  • 3+ years of hands-on experience in software development, automation engineering, or AI systems

  • Proficient in Python and/or JavaScript — writes and debugs code independently

  • Hands-on experience with REST APIs, webhooks, and authentication (OAuth, API keys)

  • Experience building with LLM APIs (OpenAI, Anthropic/Claude, or similar) in real projects — not

  • just prompting tools

  • Hands-on experience with at least one automation platform: n8n, Zapier, or Make

  • Strong written English — technical documentation reviewed at screening

  • Advanced AI fluency — AI is embedded in how they design, build, and ship systems

  • Available during client business hours — time zone overlap required

  • Preferred

  • Experience with GoHighLevel (GHL) at the API or workflow level

  • RAG experience — retrieval-augmented generation, vector databases, or persistent memory

  • GitHub portfolio or demo showing an AI agent or automation built and running in production

  • Experience in a client-facing, agency, or embedded role

  • Background in fitness tech, SaaS, or service business operations — understands real business

  • context

  • Familiarity with cloud infrastructure (AWS, GCP, or Azure) for deploying lightweight agents

  • Tools & Platforms

  • LLM APIs: OpenAI (GPT-4o), Anthropic Claude API, Gemini, Mistral

  • Automation: n8n, Zapier, Make (Integromat)

  • Languages: Python, JavaScript (Node.js)

  • APIs & integration: REST APIs, webhooks, OAuth, Postman

  • Vector / memory: Pinecone, Weaviate, Chroma, or similar

  • CRM / ops tools: GoHighLevel, HubSpot, Airtable — at API level

  • Dev tools: GitHub, VS Code, Cursor, GitHub Copilot

  • Cloud: AWS Lambda, Google Cloud Functions, or similar

  • Communication: Slack, Zoom, Google Workspace

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