LLM Application Engineer

R$225.547 (BRL)/yr

R$108,44 (BRL)/hr

R$9.744 (BRL)/yr

The average llm application engineer gross salary in Brazil is R$225.547 or an equivalent hourly rate of R$108. In addition, they earn an average bonus of R$9.744. Salary estimates based on salary survey data collected directly from employers and anonymous employees in Brazil. An entry level llm application engineer (1-3 years of experience) earns an average salary of R$159.796. On the other end, a senior level llm application engineer (8+ years of experience) earns an average salary of R$259.998.

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Salary Potential

R$254.029 (BRL)

13 %

Based on our compensation data, the estimated salary potential for LLM Application Engineer will increase 13 % over 5 years.

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Country Overview

Brazil

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

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Brazil, officially the Federative Republic of Brazil, is the largest country in South America. It is also the world's fifth-largest country by area and the seventh-largest by population, with over 213 million people. Brazil is a federation composed of 26 states and a Federal District, which hosts the capital, Brasília. Its most populous city is São Paulo, followed by Rio de Janeiro. Brazil has the most Portuguese speakers in the world and is the only country in the Americas where Portuguese is a

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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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