人工智能自动化与流程工程师
AI Automation & Workflow Engineer
AI自动化与流程工程师
也称为：AI构建师 · AI专家 · 集成专家 · 流程工程师 - 数据分析师
一位高级技术人才，从零开始构建AI驱动的系统——编写代码、连接API、部署代理，并确保所有内容在生产环境中正常运行。
领域详情
行业 AI工程 · 自动化 · 系统集成 · 技术运维
级别 高级 · 3年以上实际技术经验
教育 计算机科学学位（或同等技术学位）
编程要求 —— 至少掌握Python和/或JavaScript
AI熟练度 高级 —— 使用AI API构建，而不仅仅是使用AI工具
薪资 $12–13/小时 USD · 最高待定
类型 全职 · 每周40小时 或者 兼职 - 每周20小时
时间 客户业务时间 —— 需要时区重叠
地点 远程 · 全球
他们做什么
构建自动化系统
使用Zapier、Make或n8n设计并构建端到端自动化流程
通过REST API和webhooks连接平台——不只是拖放式集成
当无代码工具无法完成任务时编写脚本（Python或JavaScript）
部署和监控系统，使其无需持续关注即可运行
AI与代理开发
使用OpenAI API、Claude API（Anthropic）或其他类似LLM API构建AI代理
设计代理逻辑——记忆、决策树、工具使用和上下文管理
将AI整合到实际业务流程中：潜在客户资格审核、内容生成、支持、报告
当代理需要记忆时使用RAG（检索增强生成）或记忆层
系统与集成
通过API连接CRM、数据库、通信工具和自定义平台
在API层面与Airtable、HubSpot、GoHighLevel等工具合作
处理数据流、错误处理和边缘情况——不只是顺利路径
通过GitHub进行版本控制并保持代码整洁且有文档
文档与交接
编写清晰的操作规程和技术指南，非技术人员也能实际遵循
培训客户团队使用和维护所构建的内容
确保没有黑盒系统——每个系统都有文档
日常工作中使用的AI工具
LLM API：OpenAI（GPT-4o）、Anthropic（Claude）、Mistral、Gemini —— 用于构建代理和AI功能
自动化：n8n、Zapier、Make —— 带有自定义代码步骤和API连接
向量数据库：Pinecone、Weaviate、Chroma —— 用于RAG和记忆系统
开发工具：GitHub、VS Code、Postman —— 用于构建、测试和版本控制
云服务：AWS La
查看英文原文
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
Originally posted on Himalayas