AI Automation & Workflow Engineer

Also placing as: AI Builder · AI Specialist · Integration Specialist · Workflow Engineer - Data Analyst

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

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