ClickUp Solutions Architect

Aidapt is an AI consultancy serving mid-market businesses across the Middle East and Africa.

We help companies move from "AI is interesting" to AI being part of how they actually operate.

We deliver in sprints — discovery, build, train, ship — usually inside 6 to 12 weeks per engagement.

We are a ClickUp Solutions Partner, work with Snowflake on the data side, and integrate a handful of other best-in-class platforms across workflow, data, and communications.

We do not do PowerPoint strategy.

We build the thing, train the team, and stay close enough to keep it working after we leave.

We are hiring a ClickUp Solutions Architect to lead end-to-end ClickUp builds for mid-market clients and design the agentic AI layer that sits on top of them.

You will own the technical design and delivery of multiple parallel client engagements, shape new opportunities alongside the business development team, and codify reusable patterns into our delivery playbook so the practice scales beyond any one person.

You will be one of the most technical people in the company on workflow automation, working closely with the Senior AI Engineer, and expected to make architecture calls without supervision.

Workspace architecture.

Design ClickUp workspaces for clients of 50 to 500 users.

Make the foundational calls: hierarchy, spaces, custom statuses, custom task types, custom fields, permissions model, sharing logic.

Get these right and everything on top works; get them wrong and nothing does.

Automation and integration.

Build native ClickUp Automations, plus integrations to client systems via Zapier, Make.com, n8n, and the ClickUp API.

Connect ClickUp to CRMs, billing systems, communication platforms, and data warehouses.

Agentic AI layer.

Design and ship AI agents inside and around ClickUp — using ClickUp Brain, Super Agents, and n8n-based agentic workflows where ClickUp alone is not enough.

This is where the role separates from a traditional ClickUp consultant.

You will work with LLM APIs (Claude, OpenAI), retrieval-augmented generation patterns, and structured prompt design.

Discovery and scoping.

Run technical discovery on new prospects.

Translate messy business workflows into a buildable scope, an honest timeline, and a realistic effort estimate.

Push back on bad scope before it becomes a delivery problem.

Client-facing delivery.

Lead sprint reviews.

Train end users.

Handle the technical questions that come up post-go-live.

You will be in front of clients regularly — this is not a back-room implementation role.

Reusable patterns.

Capture every solution into a template, SOP, or playbook so the next architect we hire does not have to solve the same problem twice.

This is how the practice scales.