Mateo
Full Stack Developer
ReactNode.jsPythonTypeScriptNext.jsMongoDBAWSAIAPIs
Shakers for companies
Work with a senior Context Engineer
A certified context engineer for the most common complaint about internal AI: it doesn't know your business. They design the data the model receives in every answer: RAG, memory and knowledge curation, with the right context in the right window.
Senior tech talent for your knowledge layer, starting in days on the systems you already have.
- Certified talent in AI and agent skills
- Meet up to 3 AI Builders in 72 h
- Flexible collaboration models
+600
European clients across different industries
Top 4%
We work with the top 4% of certified talent in our community
72 hours
Meet 3 certified candidates in under 72 h
4.7/5
Our clients' satisfaction on Trustpilot
The talent mix your company needs
At Shakers you will find AI Engineers, Context Engineer and specialists across Tech, Product and Data
Ana
DevOps Engineer
DockerCI/CDAWSAzureKubernetesTerraformAmazon Bedrock
Lucas
Backend Developer
Node.jsPythonJavaGoPHPMySQLMongoDBDocker
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Emma
Security Engineer
Burp SuiteOWASP ZAPMetasploitNmapNessusTrivySnyk
Context Engineer: what this role brings to your project
A context engineer designs the system that feeds the model's window: which documents the RAG retrieves for each question, what conversation memory remembers, which business data gets curated before reaching the model. Anthropic coined the term; the trade existed: the natural evolution of RAG.
The difference with the prompt engineer: the prompt sets behaviour; context decides what the model knows answering. Poor context makes the model improvise; good context makes it decide.
RAGretrievalmemoryembeddingsvector DBMCPgroundingdata curationPythonLangChaincontext windowcontext evaluation
One provider. One contract. Full traceability
How Shakers works for your company
Post your project
Tell us about the project, its scope, the expertise you need and when you want to get to work.
You get three options
We match your brief against certified talent and introduce the three AI Builders who fit best.
The last word is yours
Meet the three specialists and choose who you collaborate with; we handle the rest.
Why work with Shakers
The advantages of adding this profile with Shakers
Your AI stops improvising with RAG
Answers rest on your real documents, not the model's memory: fewer hallucinations and citations that exist.
RAG over your sources, measured
Retrieval gets evaluated: which document reached the window for each question and whether it was the right one.
Memory with judgement
What the conversation remembers and what expires: memory is designed, not accumulated until the window overflows.
Curated knowledge, not a dump
Expired, duplicated and ownerless documents stay out of the window: what poisons context doesn't get in.
Verifiable grounding
Every important answer traces its source: the data sustaining it and when it was last updated.
Context at the right cost
Not every question needs all the knowledge: routing decides what context each case deserves, with the bill in view.
Frequently asked questions
Any other questions? Our team will answer them.
Tell us your data projectWhat's the difference between prompt and context engineering?
The prompt sets how the model behaves; context decides what it knows when answering. A good prompt with poor context improvises: they cross paths on every project.
What does a Context Engineer actually do?
Designs what data the model receives in every answer: what the RAG retrieves, what memory remembers, which sources get curated and what gets measured to know context arrived complete.
What does a context engineer need to start?
Access to your knowledge sources, the use cases where your AI fails and one session to prioritise. With that, the diagnosis of what the model receives arrives in days.
Context Engineer or AI Engineer?
The AI Engineer builds and integrates the model; the context engineer decides what knowledge reaches it. They cross paths on every real project: one serves capability, the other feeds it.
Can context engineering projects be done remotely?
Almost all: sources are accessible and sessions with the team happen remotely. Only the initial discovery occasionally asks for presence.
How quickly can the first RAG be working in production?
With access to sources and prioritised use cases, the first RAG over real documentation works in days. Full knowledge curation consolidates in phases.
What gets delivered in the first weeks
A diagnosis of what your model receives today, a map of the sources it should receive, and the first RAG over real documentation, with measurement of whether context arrived complete.
The layers the AIO explains, translated into work
The five-layer framework every vendor cites becomes work: what gets retrieved, remembered, contributed by tools, curated and measured. 171 live UK tech vacancies already mention context engineering, according to Shakers' market analysis (n=39,811, September 2026).
The symptom that gives it away
Your AI hallucinates internal policies, cites documents that don't exist or answers like it's their first day. The model is almost never the problem: it's the context.
Curation, not just pipelines
Half the trade is deciding what does NOT enter: expired, duplicated and ownerless knowledge that poisons the window.
Connect with AI specialists to build your next project
Find specialists in Tech, Product, Data to complement your team
AI Agent Developer
The agents consuming your context: whoever orchestrates the tools needs the window designed well and measured.
Prompt Engineer
Sets the behaviour of the model your context feeds: the how is theirs, the what-it-knows is yours to design.
AI Engineer
Integrates the model receiving your context: the API, inference and product layer where it all meets.
Backend Developer
The APIs and databases your knowledge originates from: when clean data must come from development, it's their brief.
The AI talent you need Certified by Shakers
We introduce you to three ready_to_build AI Builders in 72 hours.
