Make Developers

Somewhere between 50 and 75% less than a comparable British hire when salary, employer national insurance, pension, recruitment fees and overheads are all included. We hire UK-based automation specialists where that is what a client wants. More often the best value sits in Eastern Europe, the Philippines or Latin America, matching Britain's standard at a much lower cost, and Eastern Europe is only an hour ahead of London. In Britain, Make.com expertise mostly lives inside automation consultancies that bill by the project, so ongoing in-house capability is expensive to keep.

Make is a visual automation platform that connects the tools a business already runs, building workflows, called scenarios, without traditional code. Teams use it to stop paying skilled people to move data by hand, syncing CRM records, routing orders, chasing invoices, stitching SaaS tools together through their APIs. The scenario builder handles branching, error paths and data transformation with more depth than most no-code tools, and it has added AI modules, so scenarios can now call models to classify and draft. Complex logic gets hard to read on a canvas, and business-critical automations need the same care as production software.

Look for systems thinking above tool knowledge, because a Make expert's real job is redesigning a process so it deserves to be automated. Clicking modules together is learnable in a week. The durable skills are API literacy, reading documentation, understanding webhooks and rate limits, plus data discipline, so mappings survive the messy records real systems contain. Error handling separates professionals from hobbyists, a scenario that fails silently is worse than none. AI matters here twice, strong candidates reason through edge cases, and know when an AI module's unreliability makes it wrong.

Give a Make candidate a broken process, not a build task, and ask them to fix the process first, because that ordering is the whole discipline. Describe a real workflow with its exceptions and ask how they would automate it, listening for the questions they ask before proposing scenarios, who owns the data, what happens when a step fails. Have them read an unfamiliar API's documentation live and sketch the integration. Ask where they would use Make's AI modules and how they would guard against a model mis-classifying something. The red flag is dragging modules before understanding the process.

Demand for Make skills is growing steadily as mid-sized businesses realise their operations run on manual glue, though it is a narrower market than traditional development. The wider automation wave is accelerating it, and AI has raised the ceiling, since scenarios can now include judgement-like steps, making automation viable for processes that used to need a person for everything. Make suits organisation-wide plumbing among mainstream SaaS tools, and is the wrong home for product features needing full control. One automation is a task, a backlog across departments is a role.

Yes, our Make specialists use AI tools, both to build automations and inside them, and soundness comes from testing scenarios the way engineers test code. That means running real and edge-case data through every path, building error routes that alert rather than swallow, and documenting what the automation assumes. Where a scenario embeds an AI step, classifying tickets or drafting text, the discipline doubles, outputs that matter get validation rules or human review, since a confidently wrong model can quietly damage data at scale. We assess every candidate on whether they use AI tooling well.

Make specialists go through the same CTO-led vetting as our software engineers, because we want automation built with engineering discipline, not enthusiasm. The four stages are a technical assessment, a live pairing session with a senior engineer, a cultural fit screen and our own psychometric assessment designed for software engineers. In pairing we watch process decomposition, API reasoning and error thinking, the substance under the visual canvas. AI supports our screening, and a human makes every hiring decision. You interview matched candidates within 7 working days, and 97% stay beyond two years.

You are typically interviewing matched candidates within 7 working days of a requirements call, and developers are often embedded and pushing code within about two weeks. From there it is a rolling monthly contract with 30 days' notice, one monthly fee, and no placement charges. You can scale up or down as the work changes, and you pay nothing to interview.

There is a two-week money-back guarantee, and if you want to continue we replace the developer free of charge. In practice this rarely comes up, because you interview a shortlist of two candidates who have already passed a CTO-led technical assessment and a live pair programming session, so the fit question is largely settled before anyone starts.