Hire Claude developers
Engineers who have taken Claude past the demo and kept it running afterwards.
What you get
4 things that decide this
- 01Senior engineers only. Claude work fails on prompt design and evaluation judgement, which is not a junior skill.
- 02Production experience with the Claude API, the Agent SDK and MCP, in systems that have real users.
- 03You interview every engineer before they join, and you can say no.
- 04The team stays after launch under an agreed service level, or trains yours to take it over.
What a Claude engineer actually does here
Very little of it is prompt writing. The work is deciding what the model should never be trusted to do alone, then building the structure around it. Retrieval that returns the right passage. Tool definitions the model cannot misuse. Evaluations that catch a regression before a customer does.
PremiumAudit is a working example. Claude reads insurance premium-audit documents and validates the figures, inside a workflow where a human auditor stays in the loop. On Go4Gr8 we used MCP to give a leadership coaching platform access to tools without handing it the keys to everything.
- 01Retrieval design, so the model reads the right thing rather than more things.
- 02Tool and MCP server design, including what the model is not allowed to call.
- 03Evaluation harnesses, so a prompt change is a measurable event.
- 04Cost and latency control: caching, model routing, and knowing when a smaller model is correct.
What we have shipped
Counts you can check on this site
22
case studies published, each naming the client and the stack
2
systems built on the Claude API: PremiumAudit and Go4Gr8
1
of those running MCP in production
Where this matters most
Document work
Extraction and validation from messy real documents, where the failure mode is confident nonsense rather than an error message.
Agents that act
Systems that call tools and change state. The design question is what happens when a step fails halfway, not what the prompt says.
MCP servers
Exposing your internal systems to a model with a boundary you control, rather than pasting data into a context window.
Evaluation
The part teams skip. Without it, nobody can tell whether last week's prompt change made the system worse.
- RetrieveThe right passage, measured.
- ConstrainTools it may and may not call.
- EvaluateCases from real failures.
- ObserveCost, latency, what it read.
- RecoverRollback, and a deprecation plan.
Prompt writing is the smallest part. This is the work that decides whether the system survives its first month.
Claude in production
“They will treat your vision like their own and build it that way.”
Ron Klabunde · Founder, SmartREI ↗
Three ways to get Claude work done
| Criterion | Marketplace or freelancer | An embedded team |
|---|---|---|
| Who you meet | A profile and a rate. | The engineers, before they start. You can decline any of them. |
| Evidence | Hours billed on the platform. | Named systems in production, with the mechanism described. |
| When the model is deprecated | Your problem. The contract ended. | An eval suite that tells you within an hour whether the swap is safe. |
| After launch | Engagement closes. | An agreed service level, or a handover with your team trained. |
| Where the code lives | Often theirs until final payment. | Your repository from day one. |
How hiring works
- 01
Call
Forty-five minutes on what you are building and what has already failed. We tell you if this is not a Claude problem.
- 02
Interview
You meet the engineers who would do the work and you decide. Nobody arrives unseen.
- 03
Embed
They join your standups, your repository and your review process. Not a black box that returns a build.
- 04
Stay
An agreed service level after launch, or a handover with your team trained to run it.
The stack
Models
Retrieval
Runtime
Quality
On stage, and on the floor
Common questions
01How senior are the engineers?
Senior only. The work that decides whether a Claude system survives contact with users is judgement about failure modes, retrieval quality and evaluation design. That is not something we ask a junior engineer to learn on your project.
02Do we interview them ourselves?
Yes, and we would be worried about any vendor who said otherwise. You meet the specific engineers before they start and you can decline any of them.
03Can they work with our existing team?
That is the normal arrangement. They join your repository, your standups and your review process, and your engineers review their pull requests. Embedding is more useful than a black box that returns a finished build.
04What happens after launch?
One of two things, agreed before we start. Either we stay under a defined service level, or we hand over to your team with the evaluation suite and the runbook, and train them on it. What we will not do is disappear and leave the model unmonitored.
05Do you work with OpenAI models too?
Yes. Most of our production AI work uses the OpenAI API, and several systems use both. Picking the model is an engineering decision that follows the problem, not a loyalty we bring with us.
