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Senior Enterprise AI Engineer (AWS Bedrock)

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EMP:Technology
LATAM, Argentina, Brazil, Mexico
Tiempo Completo
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Descripción

Join Our Team Oowlish, one of Latin America's rapidly expanding software development companies, is seeking experienced technology professionals to enhance our diverse and vibrant team.

As a valued member of Oowlish, you will collaborate with premier clients from the United States and Europe, contributing to pioneering digital solutions.

Our commitment to creating a nurturing work environment is recognized by our certification as a Great Place to Work, where you will have opportunities for professional development, growth, and a chance to make a significant international impact.

We offer the convenience of remote work, allowing you to craft a work-life balance that suits your personal and professional needs.

We're looking for candidates who are passionate.

Acerca de

technology, proficient in English, and excited to engage in remote collaboration for a worldwide presence

About the Role: We are looking for an experienced Senior Enterprise AI Engineer to design and build enterprise-grade AI solutions that automate complex business workflows using AWS Bedrock and modern cloud technologies.

This role focuses on developing end-to-end AI-powered automation workflows that integrate enterprise systems such as ServiceNow and SAP while leveraging Retrieval-Augmented Generation (RAG), knowledge bases, and Responsible AI practices.

The ideal candidate combines strong software engineering.

Habilidades

with hands-on experience building AI-powered enterprise applications, integrating complex business systems, and designing scalable cloud-native architectures

Responsabilidades

: Design and develop enterprise AI solutions using AWS Bedrock

Build AI-powered workflow automation for complex business processes.

  • Develop AI agents using AWS Bedrock Agents and Guardrails.

Integrate enterprise platforms, including ServiceNow and SAP.

  • Develop secure REST API integrations across enterprise applications.

Build Retrieval-Augmented Generation (RAG) pipelines using enterprise knowledge bases.

  • Develop.

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