AI Engineer – Mid-Level

GOL Linhas Aéreas

. Develop and enhance AI agents using Large Language Models (LLMs), from conception through production deployment.

Posted 10/8/2026full-timeSão Paulo • BrazilMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and enhancing AI agents using Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) architectures, with a strong focus on integration, observability, and security. Proficient in collaborating with cross-functional teams to translate business challenges into effective AI solutions.

Highest-signal resume keywords

Large Language Models (LLMs)Retrieval-Augmented Generation (RAG)Python DevelopmentAI Application IntegrationCloud Environments (Microsoft Azure)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringPrompt EngineeringSQLCI/CDDockerGitAPIsTool CallingMemory ManagementContext Management

Soft Skills

Strong CommunicationCollaborative Work

Tools & Technologies

LangChainLangGraphLlamaIndexREST APIsEvaluation and Observability Tools

Industry Keywords

Generative AIAI AgentsData ProtectionWorkflow OrchestrationQuality Metrics

Tech Stack

Tools & technologies

AzureCloudDockerPythonSQL

About the role

Key responsibilities & impact

Develop and enhance AI agents using Large Language Models (LLMs), from conception through production deployment.
Build agentic workflows that enable agents to plan tasks, use tools, retrieve information, and execute actions in a controlled manner.
Develop solutions using Retrieval-Augmented Generation (RAG) architectures to connect language models with corporate data and knowledge.
Integrate LLMs and agents with APIs, databases, applications, and corporate services to enable intelligent process automation.
Develop and enhance multi-agent solutions when applicable, defining responsibilities, interactions, and orchestration mechanisms.
Implement memory, context, tool-calling, and state-management mechanisms for agent-based applications.
Build evaluation, tracking, logging, and observability mechanisms to monitor the quality, performance, behavior, and cost of AI solutions.
Implement guardrails and security mechanisms, contributing to the responsible use of models and the protection of corporate data.
Develop reusable components, templates, and standards that accelerate the creation of new AI solutions.
Conduct proofs of concept (POCs) to evaluate new models, frameworks, architectures, and Generative AI capabilities.
Support the evolution of solutions with a focus on quality, scalability, performance, security, and cost.
Collaborate with Data Science, Engineering, Architecture, and business teams to identify and implement AI application opportunities.
Keep up with the evolution of the Generative AI and Agentic AI ecosystems, evaluating technologies that may generate value for the company.

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, or a related field.
Experience developing software with Python.
Knowledge of Software Engineering, including version control, APIs, testing, and development best practices.
Experience or practical knowledge building applications using Large Language Models (LLMs).
Knowledge of Prompt Engineering and techniques for building and evaluating prompts.
Knowledge of Retrieval-Augmented Generation (RAG) architectures, including embeddings, chunking, context retrieval, and vector databases.
Experience with frameworks for developing and orchestrating AI applications, such as LangChain, LangGraph, LlamaIndex, or equivalent technologies.
Knowledge of AI agents, including tool calling, memory, context management, and workflow orchestration.
Experience integrating applications through REST APIs and external services.
Knowledge of SQL and the handling of structured and unstructured data.
Knowledge of Cloud environments, preferably Microsoft Azure.
Knowledge of CI/CD, Docker, and Git practices applied to application development and deployment.
Knowledge of evaluation and observability for LLM applications, including quality, performance, and cost metrics.
Familiarity with security applied to Generative AI, including guardrails, data protection, and prompt-injection mitigation.
Ability to translate business problems into AI-based technical solutions.
Strong communication skills and the ability to work collaboratively with technical teams and business areas.

Benefits

Comp & perks

Travel Benefit: domestic and international airfare at special discounts for you, your family, and friends
Health insurance
Dental insurance
Group life insurance
Meal voucher
Food allowance
Transportation allowance
Wellhub or TotalPass
Partnerships club with hundreds of participating companies
Birthday day off
Profit-sharing bonus (PPR)