AI Automation & Workflow Engineer

AI Automation & Workflow Engineer - Seamlessassist | Career Page

AI Automation & Workflow Engineer

Chisinau, Moldova

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Job Openings AI Automation & Workflow Engineer

About the job AI Automation & Workflow Engineer

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

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