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, General

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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📌 AI Automation & Workflow Engineer (Bogotá, D.C.)
🏢 SeamlessAssist
📍 Bogotá, D.C.