LLM Application Engineer

210.579 RON (RON)/yr

101,24 RON (RON)/hr

9.097 RON (RON)/yr

The average llm application engineer gross salary in Romania is 210.579 RON or an equivalent hourly rate of 101 RON. In addition, they earn an average bonus of 9.097 RON. Salary estimates based on salary survey data collected directly from employers and anonymous employees in Romania. An entry level llm application engineer (1-3 years of experience) earns an average salary of 148.665 RON. On the other end, a senior level llm application engineer (8+ years of experience) earns an average salary of 241.423 RON.

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Salary Potential

310.740 RON (RON)

48 %

Based on our compensation data, the estimated salary potential for LLM Application Engineer will increase 48 % over 5 years.

Education

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Country Overview

Romania

Cost of living is calculated based on accumulating the cost of food, transportation, health services, rent, utilities, taxes, and miscellaneous.

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Romania is a country in Southeast and Central Europe. It lies on the lower course of the Danube, north of the Balkan Peninsula, and on the northwestern shore of the Black Sea. It borders Ukraine to the north and east, Hungary to the west, Serbia to the southwest, Bulgaria to the south, Moldova to the east, and the Black Sea to the southeast. It is the twelfth-largest country in Europe by area, covering 238,397 km2 (92,046 mi2), and the sixth-most populous member state of the European Union, wi

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Disclaimer
This page is an excerpt of the much more complete compensation information available in ERI's Assessor Series.

ERI's compensation data are based on salary surveys conducted and researched by ERI. Cost of labor data in the Assessor Series are based on actual housing sales data from commercially available sources, plus rental rates, gasoline prices, consumables, medical care premium costs, property taxes, effective income tax rates, etc.

Job Description
Designs, builds, and optimizes production applications powered by large language models (LLMs). Integrates LLMs with internal systems and external services to deliver reliable, safe, and cost-efficient AI capabilities across search, summarization, generation, and agentic workflows. Collaborates with Product, Data, and Platform teams to translate use cases into robust retrieval-augmented generation (RAG) pipelines, evaluation harnesses, and monitoring that meet latency, quality,..., and governance targets. Designs LLM application architectures, including orchestration layers, context construction, and tool/API integrations. Implements retrieval-augmented generation pipelines using embeddings, vector databases, and document chunking strategies tuned to domain content. Engineers prompts, guards, and system instructions; versions prompt assets and curates reusable prompt libraries for common tasks.Read More
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