Job Description
Job Description
Remote | Client-Facing | n8n + Claude Code + MCP | Real Implementation, Not Demos
Are you tired of AI roles that focus on demos and POCs that never make it to production? Do you get frustrated watching businesses struggle with manual processes while perfectly good automation solutions exist? Can you bridge the gap between "cool AI demo" and "reliable system that runs every day without breaking"?
If you want to ship real automations that save real companies real money—in weeks, not quarters—this role at Kiingo AI is for you.
Why This Role is Different
We're not building foundation models or chasing the latest AI hype. We're implementing practical automations for SMBs that need to scale operations without proportionally increasing staff. Our clients are CEOs and executives who need results they can measure, systems they can trust, and ROI they can prove.
This is implementation engineering: using n8n, Claude Code, and MCP to build automations that handle real work, preserve institutional knowledge, and create competitive advantages that compound monthly.
What You'll Build
As our AI Engineer, you'll design and ship client automations that transform how businesses operate—with proper guardrails, monitoring, and handoff documentation.
✔ Orchestrate Complex Workflows: Design multi-step n8n automations that handle exceptions, retry gracefully, and alert humans when needed
✔ Create Safe AI Agents: Build agents with tool calling, memory, and human-in-the-loop approvals for any risky actions
✔ Connect Business Systems: Wire together CRMs, ERPs, and legacy tools using MCP servers and secure APIs
✔ Implement Guardrails: Add schema validation, refusal rules, and audit trails so nothing breaks in embarrassing ways
✔ Measure Real Impact: Track cycle time reduction, error rates, and hours saved—then prove the ROI
✔ Enable Non-Technical Users: Create runbooks and training so clients can operate what you build
The Tools You'll Master
You'll work hands-on with modern AI implementation tools:
n8n – Visual workflow automation with code flexibility when needed
Claude Code – AI-powered coding assistant for scaffolding and refactoring
MCP (Model Context Protocol) – Connect LLMs to tools and data securely
Standard AI Stack – OpenAI/Anthropic APIs, function calling, structured outputs
Business Systems – QuickBooks, HubSpot, Google Workspace, legacy apps
Observability – Logging, monitoring, alerting (because production matters)
Who You Are
✅ Builder with Judgment – You ship fast but know where to add safety rails
✅ Systems Thinker – You see patterns and build reusable solutions
✅ Client-Friendly – You can explain complex tech to executives clearly
✅ Reliability-Obsessed – Your automations handle edge cases and fail gracefully
✅ Outcome-Focused – You measure success in hours saved and errors prevented
✅ Documentation Believer – You leave behind runbooks others can actually follow
Your First 90 Days
Day 30: Ship internal automation saving 5+ hrs/week, shadow 3 client sessions, build first MCP server
Day 60: Deploy 2 client automations with proven ROI, create reusable templates, support Bootcamp
Day 90: Own 5+ production automations, build industry vertical package, prototype advanced agent
Hard Skills We Need
Must-Have:
- Built 3+ real automations end-to-end (any platform: n8n, Zapier, Make, or code)
- Comfortable with APIs, webhooks, JSON schemas, and basic JavaScript
- Experience with LLM integration (prompting, function calling, structured outputs)
- Git basics, Docker basics, and writing clear documentation
- Understanding of retries, idempotency, and error handling
Nice-to-Have:
- MCP server authoring experience
- RAG/vector database implementation
- Computer Use API for legacy system automation
- Azure cloud services (our stack)
- SQL and data transformation skills
Soft Skills That Matter
- Discovery & Facilitation: Run tight client sessions that extract real requirements
- Problem Decomposition: Break vague requests into testable milestones
- Security Instincts: Spot risky patterns and propose safer alternatives
- Change Management: Help teams adopt new workflows without resistance
- Stakeholder Communication: Keep executives informed without overwhelming them
What Makes This Special
Real Implementation – Ship to production, not PowerPoint
Measurable Impact – Every automation has clear before/after metrics
SMB Focus – Help businesses that need it most, not just enterprises
️ Build the Practice – Define how AI implementation should work
Growing Market – Be early in the massive SMB AI adoption wave
About Kiingo
We're the AI consultancy that actually implements. While others deliver recommendations, we help you do it
Based in Irvine, we serve executives through Vistage peer groups and direct engagement. Our founder Ross Hartmann brings 10+ years in AI and a practical, results-first approach.
How to Apply
Send to: ross at kiingo dot com
Subject: AI Engineer – [Your Name]
Include:
- Resume highlighting automation/integration experience
- Brief description (or video) of one automation you've built: the problem, solution, and measured impact
- BONUS: Link to a simple n8n flow, MCP server repo, or documented automation you've created
Quick Test: In 2-3 sentences, explain how you'd add a human approval step before an AI agent sends 100 customer emails.
P.S. – If you read this and thought "finally, a role about making AI actually useful for real businesses"—you're exactly who we're looking for. We promise you'll never have to build another chatbot that nobody uses.