Experienced AI Automation Engineer — Intelligent Timeline & Work Planning | n8n, Airtable, Website
We’re looking for a technically strong automation engineer to build a production-grade Intelligent Timeline Engine that converts assigned work + rubric requirements into a structured execution plan.
This is not a basic task generator or template automation. We want a clean, modular, observable workflow that models scope, milestones, and execution risk in a structured way.
Objective:
Given:
- Assignment description
- Rubric or evaluation criteria
- Deadline
- Optional constraints (workload, priorities)
The system should:
- Parse scope and complexity
- Break work into milestone phases
- Estimate realistic durations
- Identify likely obstacles or bottlenecks
- Apply buffer logic based on risk
- Output a structured timeline and risk summary
Technical Expectations:
- Built using n8n (or similar orchestration platform)
- AI integration (OpenAI / Claude) for scope modeling
- Structured persistence layer (Airtable, Supabase, or similar)
- Clean workflow design with modular nodes
- Error handling, retry logic, and structured logging
- Webhook or form-based intake
- Slack or email output formatting
Bonus:
- Configurable buffer percentages
- Historical workload awareness
- Deadline stress detection
- Clean documentation + Loom walkthrough
Deliverables:
- Fully functioning workflow
- Database schema
- Cleanly documented system architecture
- Short handoff walkthrough video
- Scalable structure (not a one-off demo)
We are not looking for:
- Template-based automations
- Surface-level prompt wrappers
- Fragile “works on my machine” builds
We are looking for someone who thinks in systems and understands structured automation architecture.
Please include:
1 Examples of production automation systems you’ve built
2 How you handle workflow observability and failure recovery
3 Estimated timeline to delivery
Apply Now
Apply Now