AI Automation & Workflow Engineer
Confirmed on the employer's own hiring board on Nov 13, 2026. First seen by Alion on Nov 13, 2026.
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 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