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AI projects in production
Work as an AI Engineer
Join Shakers' on-demand collective of expert talent: real AI projects, verified clients and a project-based way of working.
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 blended human + agent teams, choose what you take on and bill according to your seniority. AI matching brings you projects that fit your stack.
- Real projects with verified clients
- Clear, on-time payments
- A collective of expert talent
Shakers
AI in production, not prototypes: real projects, project-based.
Over 600 European companies trust Shakers
The profile, explained
What this profile does and the projects it runs at Shakers
As an AI Engineer at Shakers you design and ship AI applications for clients who already have the project defined: you integrate LLMs, build RAG pipelines and orchestrate agents in production. You work project-based inside blended human + agent teams, choose what you take on and bill according to your level. You join a collective of verified expert talent, with AI matching that connects you to projects that fit your stack and your rate.
OpenAI APIAnthropic ClaudeGoogle GeminiLangChainLlamaIndexLangGraphRAGPineconeWeaviatepgvectorFastAPIPythonTypeScriptNext.jsLangSmithDocker
What an AI Engineer does and the projects they run
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.
RAGAgentsLLMsEvalsObservability
Free to join, no hidden fees
How Shakers works for talent
Verification (vetting)
You go through our peer vetting process to join the collective of expert talent.
Matched with projects
Our AI connects you with projects from verified clients that fit your profile and your rate.
Kick off the project
You choose what to work on, agree the scope and start working project-based.
Grow within the collective
You build up projects, reviews and access to higher-responsibility engagements.
Vetted talent from the Shakers collective
Experts already delivering the kind of projects you are looking for
Work project by project, friction-free
You focus on the project; we take care of the rest
You receive the projects that match your stack
No time wasted searching, no technical tests nobody knows how to assess. You decide which ones to join.
Contracts, tax and compliance covered
Never invoiced on your own? No problem: we handle it end to end so you can focus on the code.
Every payment on time, no chasing anyone
Shakers manages the client relationship, milestones and payments. Clear, on-time income on every project.
Everything about this profile
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 blended 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.
In short
- Contract AI Engineer, project-based, with AI running in production.
- You choose projects that fit your stack; AI matching brings them to you.
- You bill according to seniority, with contracts and payments handled by Shakers.
What an AI Engineer does on a Shakers project
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.
AI skills Shakers validates before the match
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.
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.
Shakers, in numbers
+600
European clients across industries
+14.000
Talents apply; we only work with the vetted 4%
+3.000
Projects published on Shakers
72h
To get your best-fit match
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.
Take the next step with Shakers
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