AI Engineer

IEBT Innovation

Engineer developing and deploying generative AI systems in hybrid setting. Collaborating on connectors and APIs for integrating AI models into corporate systems.

Posted 7/16/2026full-timeBelo Horizonte • 🇧🇷 BrazilMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying Generative Artificial Intelligence systems, with a strong focus on prompt engineering, RAG architectures, and integration with enterprise systems. Proficient in Python and familiar with best practices in software engineering and MLOps.

Highest-signal resume keywords

Python ProficiencyGenerative AI FrameworksVector Database ExperienceAPI Integration SkillsMLOps Knowledge

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonPrompt EngineeringRAG Architecture DesignSoftware Engineering Best PracticesMLOpsFew-Shot Prompting TechniquesFine-Tuning ApproachesStateful AI DevelopmentAutonomous AI DevelopmentCost Optimization for LLM API Calls

Tools & Technologies

LangChainLlamaIndexLangGraphChromaDBPineconeQdrantPgvectorGitDockerRESTful APIs

Industry Keywords

Generative AIMulti-Agent AIEnterprise SystemsCRMsERPsE-Commerce PlatformsGovernanceSecurityReduction of HallucinationsLLM Providers

Tech Stack

Tools & technologies

DockerGRPCPython

About the role

Key responsibilities & impact

Develop and deploy Generative Artificial Intelligence systems and multi-agent AI agents (stateful and autonomous).
Design and optimize RAG (Retrieval-Augmented Generation) architectures using vector databases to build intelligent knowledge bases.
Develop and test advanced prompt engineering strategies, few-shot prompting techniques, and fine-tuning approaches for foundation models.
Collaborate on building robust connectors and APIs to integrate AI models with enterprise systems such as CRMs, ERPs, and e-commerce platforms.
Ensure governance, security, reduction of hallucinations, and cost optimization for LLM API calls.

Requirements

What you’ll need

Strong proficiency in Python for software and AI development.
Experience with generative AI orchestrators and frameworks: LangChain, LlamaIndex, or LangGraph.
Familiarity with consuming APIs from LLM providers (OpenAI, Anthropic, Google Vertex AI).
Hands-on experience with vector databases (ChromaDB, Pinecone, Qdrant, pgvector, etc.).
Knowledge of software engineering best practices (Git, Docker, RESTful APIs/gRPC) applied to AI (basic MLOps).

Benefits

Comp & perks

Health and Dental Insurance
Transportation allowance
Home office allowance
Meal allowance
Paid vacation
Day off on your birthday
Health and Wellness program
Individual Development Program (IDP)