Álvaro
Data Scientist
“In a climate this uncertain, Shakers gives you a layer of reassurance and confidence. What I like most, without a doubt, is the flexibility and getting to work on top-tier projects.”
Join ShakersAI projects in production
Work as an AI Engineer
You integrate LLMs, build RAG over internal data and take agents to production. Shakers connects you with projects aligned with your stack, day rate and availability, with more flexibility and better terms.
As a contract AI Engineer at Shakers you take language models to production for clients with already-defined projects: LLM integrations, RAG systems and agents that solve a real case, not a demo.
You work project-based inside human + agent teams, choose what you take on and bill according to your seniority. AI matching brings you projects that fit your stack.
- Higher-paying projects
- More continuity between projects
- Greater recognition for your experience
+3,000
Tech projects published on Shakers
+90
Tech, Product and Data specialisms are part of Shakers
6 months
Average length of a project with Shakers
4.7/5
Our AI Builders' satisfaction on Trustpilot
AI Builder careers powered by Shakers
See how other AI Builders access better projects, build their reputation and grow their careers.
Amelia
AI Agent Developer
“I have been building AI agents for years. Thanks to Shakers I stopped chasing clients and started genuinely choosing which projects I wanted to work on. I work with some of the best companies in Europe, at my own rate, and I focus on what I am good at and what I love: building.”
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Luz
Backend Developer & Data Engineer
“Shakers adds a lot of value because it connects you with sharper projects, already filtered and better defined. It saves you a big part of the upfront work of understanding the client, quoting and weighing up whether it is worth it, and that means that as a contractor you can go far more directly to the opportunities that genuinely fit you.”
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Rubén
Software Developer
“Life as a contractor has a lot going on and it is not always easy. We like to focus on what we are good at, but you also have to manage clients, invoicing and go looking for work. For me, Shakers has been key because it does that prospecting for me, it gives the client confidence from the very first moment, and it lets us be part of a community with real enthusiasm.”
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Alejandro
AI Developer
“Shakers was key to getting my company off the ground: it gave me the flexibility to keep contracting while I built my next chapter. Without Shakers, I would have had to raise funding or push the project back.”
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Toño
Product Designer
“With Shakers I have landed recurring projects that give me peace of mind and room to grow professionally. It is not just about reaching quality clients: it is feeling that you have a network behind you, one that connects you with real opportunities and helps you move forward as a freelancer.”
Join ShakersWhat you can build as an AI Engineer at Shakers
An AI Engineer is the person who takes applications built on already-trained language models into production and keeps them running. They integrate an LLM through an API, build RAG (the system retrieves fragments of the company's own data and the model answers citing them) and orchestrate agents that run processes against internal APIs. They measure quality with evals and decide on cost per token and latency. Training the model from scratch is ML Engineer ground; analysing the business data is the Data Scientist's.
It's not a notebook role: it's the person who puts AI into production with judgment on cost, latency and evaluation. At Shakers you join projects where the model is already decided and the challenge is the real implementation.
Typical stack: OpenAI, Anthropic Claude, LangChain, LlamaIndex, RAG, Pinecone, pgvector, FastAPI, Python, evals with Promptfoo or LangSmith.
OpenAI APIAnthropic ClaudeGoogle GeminiLangChainLlamaIndexLangGraphRAGPineconeWeaviatepgvectorFastAPIPythonTypeScriptNext.jsLangSmithDocker
RAGAgentsLLMsEvalsObservability
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.
AI and Machine Learning 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 Engineer does and by what criteria
Take RAG and agents into real use
Chunking, embeddings, reranking and citations; orchestrating agents with real tools and automated evals using cases from the operation.
Evaluate cost, latency and hallucination
You instrument quality and cost-per-response metrics to decide which model and pattern to use, and when not to use AI at all.
Connect AI to the client's data
Ingestion into the vector store, internal APIs and traceability: the layer where most pilots never reach production.
LLMs and RAG in production
Provider APIs, RAG frameworks, vector databases and handling real limits (context window, prompt injection).
Production-grade Python
Typing, async, testing and deployment. Without this foundation, no integration survives a week in production.
Evals and technical decisions
Knowing how to measure quality and pick the simplest architecture that solves the case.
Frequently asked questions
Any other questions? Write to us and we will reply.
What kind of AI projects are there at Shakers?
Real projects from verified clients: LLM integrations, RAG systems, agents, internal copilots and taking AI to production. You choose which ones you work on.
What is the verification process like?
You go through peer vetting that validates your experience, your stack and your projects. It's what keeps the collective's quality high and clients' trust intact.
How and when do I get paid?
You agree your rate per project and get paid clearly and on time against the agreed milestones, with no hidden fees.
Can I combine it with other work?
Yes. You work project-based and set your own availability: you can collaborate part-time or full-time, depending on what you agree.
Do I need experience with agents and RAG to join?
It's what we value most: having shipped AI in production, not just in notebooks. Hands-on RAG, vector databases and quality evals count more than mastering any one framework.
Are the AI projects at Shakers prototypes or production?
Production. The client arrives with a defined case and the challenge is the last mile: integrating, evaluating and stabilizing in real operation.
The projects you'll find
At Shakers, AI projects start from a case the client has already defined: LLM integrations, RAG systems over knowledge bases, agents and internal copilots. You work on the real implementation, the point where most initiatives get stuck.
What counts
Having shipped AI in production, not just in notebooks: hands-on RAG and vector databases, quality evaluation, and judgment on cost and latency. Mastering a framework like LangChain matters less than knowing when NOT to use it.
How you work
You collaborate project-based inside human + agent teams, choose what you join and bill according to your level. AI matching brings you projects that fit your stack; you decide which ones to accept.
Roles an AI Engineer works with
At Shakers, AI projects are delivered as a team. These are the roles in the collective an AI Engineer overlaps with most.
Python Developer
Many AI projects start from Python: pipelines, APIs and automation the model is built on.
Backend Developer
The backend exposes AI to the product: APIs, queues and data. You come in alongside them when AI logic and integration move together.
AWS DevOps Engineer
The person who deploys and monitors the system in the cloud: pipelines, scaling and cost under control.
Not sure which projects fit you best? Join the collective and let AI matching bring you the ones that match your stack.
Take the next step with Shakers
Want AI projects running in production?
Create your profile and start receiving projects that match your stack.
