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Data Scientist
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Join ShakersShakers for expert talent
Work as an AI Reliability Engineer
Projects where the AI that works on Tuesday still works on Thursday are yours: what gets evaluated, what gets watched and who answers when it fails. Shakers connects you with companies with AI already in production.
The trade reads in two places: the evaluation tools catalogue and the post asking whether AI is reliable. Neither tells who sets up a real model's watch, engagement by engagement. Here is that.
- Higher-paying projects
- More continuity between projects
- Greater recognition for your experience
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Software Developer
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AI Developer
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Product Designer
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Join ShakersWhat an AI Reliability Engineer decides daily
An AI Reliability Engineer sustains AI in production: continuous model evaluation, regression watch between versions, drift detection when the world changes relative to the data, and the guardrails and traces that answer why it failed. The SRE of AI: the discipline that keeps classic systems running, applied to models that degrade silently. They don't build the model (AI Engineer): they guarantee what's built keeps working.
You decide which cases enter the evaluation battery and what gets tolerated, which metric gets watched and with what threshold, what the AI does alone and what escalates to a human. You also decide what isn't accepted: a model without traces or battery isn't in production. The model belongs to the client; working every morning, to you.
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EvalsRegressionDriftGuardrailsTracesCost per query
Free to join, no hidden fees
How Shakers works for talent
Create your profile
Tell us who you are, what you can do, the projects you want to work on and what your availability and rate are.
Get your certification
We certify your experience and your use of AI so companies understand and trust what you bring.
Match with projects
We connect you with well-paid projects that fit your expertise and your preferences.
New Roles for AI Era projects that live up to your expectations
Work on real projects, with teams that need your expertise, without wasting time looking for opportunities.
Projects that fit you
Work with companies that need your stack and experience to take their projects to production.
Opportunities that come to you
Our AI matching connects your profile with the projects that fit your preferences.
You build. Shakers handles the rest
Set your own terms based on your seniority. We manage contracts, payments and paperwork.
What an AI Reliability Engineer delivers on a Shakers project
The brief arrives with the symptom
Shakers is hiring infrastructure: the project arrives with the AI that degraded or must not degrade and its systems, not a list of technologies.
Watch you can audit
You deliver the eval battery, the metrics panel and the guardrail protocol, including the threshold you dropped and why.
What happens when the metric moves
You set who gets the alert, at what threshold it escalates to a human and who answers for the failure while it recovers.
Systems sustained, not half-watched
Having sustained models or systems in production and being able to tell which battery saved you, and what you did when it failed unannounced.
Evaluate everything or what matters
Choosing what deserves a battery and what only passive watch: measuring everything is also a way of measuring nothing.
How far your brief goes
You sustain what's built; you don't rewrite the model or the product. If the project needs building, you say so at kickoff.
Frequently asked questions
Any other questions? Write to us and we will reply.
What are evaluations of an AI model?
Real cases from your business that every model version is measured against, with explicit success criteria and LLM-as-judge where it helps. The difference between believing it works and knowing it.
How do you get into the trade from SRE or QA?
Through the natural door: you already sustained systems or measured quality; models only change the object. The certification measures whether you can set up a real model's watch.
What tools are used to evaluate LLMs?
MLflow, DeepEval or whatever the stack needs: learned in a week. The trade is what to evaluate, what to tolerate and how to answer when the metric moves.
How much does a freelance AI reliability engineer earn?
You invoice per project, and scope sets the band: battery to build, metrics to watch, guardrails to define. The budget is agreed before accepting.
Can AI reliability work be done remotely?
Almost all: panels and evaluations run in the cloud and sessions with the team happen remotely. Only the occasional kickoff asks for presence.
How do I join Shakers as a reliability engineer?
Create your profile, pass the certification process and join the collective: only 4 percent make it. Then you choose which reliability projects to work on.
The day to day of the trade
The metric that moved on a Tuesday nobody was watching, the model version that improved one thing and broke three, the trace that didn't exist when the client asked why. The trade is learned with AI in production.
The category is born and pioneers are welcome
111 live UK tech vacancies already mention llm evaluation, according to Shakers' market analysis (n=39,811, September 2026), inside AI Engineer titles. If you come from SRE or QA, this is the territory to enter first.
Judgement outlasts the tool
Arize today, MLflow tomorrow, DeepEval the day after: tools change monthly. What gets certified is the judgement: what to evaluate, what to tolerate and how to answer when the metric moves.
How people arrive
The doors: SRE and devops who already sustained systems, QA that measured everything but models, or the data scientist tired of unsupervised models.
Roles that cross a reliability project
Four roles from the collective cross your path on a reliability project, from who built the model to who sustains the infrastructure.
AI Engineer
Built what this role sustains: the model integration, API and product layer that reliability watches over.
AI Agent Developer
The agent's guardrails are designed with whoever built it: the frontier between orchestrating and sustaining gets agreed per project.
AWS DevOps Engineer
The classic operations this trade was born from: infrastructure, deployments and the SRE that has always existed in your stack.
Backend Developer
The systems the AI touches: when traceability needs hooks in the product, that's the role that puts them.
The boundaries between these roles are agreed on each project: the title does not set them.
Take the next step with Shakers
AI that doesn't fail in silence? That's yours
Pass Shakers' certification and choose your reliability projects.
