AI Engineer
One full-time AI Engineer, recruited, vetted and trained for your stack
An AI Engineer who works for you and no one else. Not an agency retainer, not a fractional consultant, not a contractor who ships a prototype and leaves you owning it. We find the person, prove they have shipped production LLM systems before you meet them, and stay involved once they start.
- Fewer than 2% of applicants are accepted
- Every shortlisted engineer is judged on a paid work sample, not a resume
- 3-4 weeks from first call to final match
- Full-time and dedicated, so they own the system after launch
- 30-day rematch guarantee
Tell us what you are building
Tell us what you are building and which parts are stuck. We take it from there.
Companies that hire through WeAssist
Fewer than 2% of applicants are accepted, and 98% of clients stay
Under 2%
of applicants accepted
98%
client retention
2.5+ yrs
average partnership
500+
families supported
Meet the founder
Reef Colman, founder and CEO, on why WeAssist exists.
Why hiring an AI engineer keeps stalling
The demo works and production does not
A retrieval prototype that answers ten questions in a notebook is not a system that answers ten thousand under load, with evals, monitoring and a bill you can defend.
US AI engineering pay is above your budget, not above your need
US AI engineering salaries price most teams out of the hire. Most teams do not need a research hire anyway. They need someone who can build and operate applied LLM systems, and that person is findable outside the US market.
An agency builds it once and bills you to fix it
Consultants hand over a repo and go. Nobody owns the retrieval quality drift, the prompt regression, the inference bill or the 2am timeout. A dedicated engineer does.
You cannot tell a senior AI engineer from a confident one
Everyone lists RAG, fine-tuning and LangChain. Very few have run an eval harness that caught a regression before a customer did, and a CV cannot show you the difference.
What they build and operate
- RAG pipeline build: chunking, embedding, retrieval and reranking
- Retrieval evaluation and regression harnesses
- Prompt orchestration, tool calling and structured output
- Guardrails, refusal handling and output validation
- Vector store setup, indexing and reindex jobs
- Fine-tuning and dataset preparation for narrow tasks
- Model serving and inference endpoints
- Inference cost tracking and prompt or model cost reduction
- Latency profiling, caching and batching
- Data pipeline and ETL work feeding the model
- Monitoring, drift detection and quality alerting
- Model and prompt version control with rollback
- Internal AI tooling and agent workflows
- Integration into your existing app, API and CRM
- Documentation and SOPs so the system is not one person's head
- Handover-ready runbooks for on-call and incidents
Ready to hire the engineer who stays after launch?
Three to four weeks to an engineer who owns the system
- 01
Discovery call
We learn the stack, the system you are building and which parts are actually blocking you.
- 02
Client success analysis
We turn that into the profile of the engineer the role needs: applied LLM build, MLOps, data engineering or a specific mix of the three.
- 03
Talent sourcing and screening
We recruit and vet against that profile. Technical candidates are assessed on systems they have shipped and operated, not on claims.
- 04
Client and talent interview
You meet the shortlist, review their work sample and code, and you choose.
- 05
Final match
Your AI Engineer starts with repo and model-key access scoped, the eval harness they inherit walked through, and 30-day milestones agreed.
30-day rematch guarantee
If the match is not working, we find a better fit at no additional cost.
Hear it from our clients
Real clients on what changed after they hired through WeAssist.
98% of clients stay. Here is what three of them report.
The smoothest change since acquiring the company
Time back at the end of the day
Fewer hats, and better sleep
Book a discovery call
Tell us what you are building and where it is stuck. We take it from there.
Questions technical founders ask before the call
- Does the talent depth actually exist offshore at this level?
- Not in volume, and we do not pretend otherwise. Engineers who have shipped and operated a production LLM system are scarce everywhere, which is why fewer than 2% of applicants are accepted and why this role takes the full three to four weeks. What we will not do is present a strong general software engineer as an AI Engineer because the title fits.
- How do I know they can do the work before I commit?
- You see the work. Shortlisted engineers are assessed on systems they have built and operated, and you review that plus their code in the interview. If a paid trial task on your own codebase is what you need to be sure, we arrange it before the match is final.
- Is this a discount hire?
- It is a different market, not a bargain bin. We price this role at the top of the local band because that is where the engineers who can carry a production system sit. If you are looking for the cheapest possible rate, we are the wrong firm and the placement would fail in month two.
- What about our code, our data and our model keys?
- Scoped access, signed confidentiality, and no local storage of your data. Access is granted per system rather than blanket, and it is set up during onboarding with your team rather than assumed. Anything your security review requires is a conversation before the start date, not after.
- How much timezone overlap will I get?
- Overlap is agreed in the role profile before we recruit, and we screen for it, so candidates who cannot hold your hours never reach your shortlist. This matters more for engineering than for admin work, because code review and incidents need a live person.
- Is this an engineer or a consultant?
- A full-time employee of your business in everything but payroll. They work for you and no one else, they stay after launch, and they own the system rather than handing it over. That is the difference from a retainer that builds once and bills you to fix it.
- What if the match is not working?
- Our 30-day rematch guarantee: if the match is not working, we find a better fit at no additional cost.