Hire AI Engineers
Hire vetted AI engineers from Tirana for a dedicated nearshore team or staff augmentation. They build LLM features, RAG and agents into real products: practical AI that ships, not demos.
What AI engineers do
- Build LLM-powered features: chat, summarisation, extraction and classification
- Implement retrieval-augmented generation (RAG) with vector search over your data
- Design and ship AI agents and tool-use workflows wired into real APIs
- Integrate model providers, manage prompts, evaluation, cost and token budgets
- Productionise AI: guardrails, observability, latency and reliability under load
Why nearshore with Square
- Full CET overlap: iterate on prompts, evals and agents live in your working day
- Fluent English and Italian; AI scoping and reviews in your language
- Multi-stage vetting on real LLM and integration tasks, not just framework familiarity
- Backend-grade discipline: AI features that are observable, cost-aware and production-ready
Frequently asked questions
How much does it cost to hire an AI engineer?
It depends on seniority and on the use case, from a single RAG feature to a full agent workflow. Rates run from EUR 35 to 55 per hour. We quote after a short call and bill monthly, with no recruiter fee or agency markup, typically well below a comparable Western European hire.
How quickly can an AI engineer start?
We usually present a vetted shortlist within about a week, and the engineer joins your team in 2-3 weeks. AI roles vary widely (RAG, agents, applied ML), so we scope your exact use case during matching to get the fit right.
Are these ML researchers or applied AI engineers?
Applied AI engineers. They build production features on top of LLMs and ML services (RAG, agents, integrations, evaluation and cost control) rather than training foundation models from scratch. The focus is reliable AI inside real products.
What about contracts and IP ownership?
Engagements are monthly with a short notice period, as a dedicated engineer or staff augmentation. You own all code, prompts, data pipelines and model configurations: no lock-in, and your API keys and data stay under your control.