LLM Application Engineer

41 486 € (EUR)/yr

19,95 € (EUR)/hr

1 792 € (EUR)/yr

The average llm application engineer gross salary in Lithuania is 41 486 € or an equivalent hourly rate of 20 €. In addition, they earn an average bonus of 1 792 €. Salary estimates based on salary survey data collected directly from employers and anonymous employees in Lithuania. An entry level llm application engineer (1-3 years of experience) earns an average salary of 29 308 €. On the other end, a senior level llm application engineer (8+ years of experience) earns an average salary of 47 341 €.

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Salary Potential

54 128 € (EUR)

30 %

Based on our compensation data, the estimated salary potential for LLM Application Engineer will increase 30 % over 5 years.

Education

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Country Overview

Lithuania

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

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Lithuania, officially the Republic of Lithuania, is a country in the Baltic region of Europe. It is one of three Baltic states and lies on the eastern shore of the Baltic Sea, bordered by Latvia to the north, Belarus to the east and south, Poland to the south, and the Russian semi-exclave of Kaliningrad Oblast to the southwest, with a maritime border with Sweden to the west. Lithuania covers an area of 65,300 km2 (25,200 sq mi), and has a population of 2.9 million. Its capital and largest city i

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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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