100 Ofertas de Ibm en Buenos Aires

Ingeniero de Redes Inalámbricas - INGLES AVANZADO Experis Ciudad Autónoma de Buenos Aires (CABA), Buenos Aires

Acerca de C&S
Somos una empresa de más de 160 profesionales, consolidada hace 38 años en el mercado. Nuestro propósito es garantizar la satisfacción de nuestros clientes; para ello, ofrecemos servicios de Desarrollo de Software, Talent Outsourcing y Consultoría IT. Contamos con certificación ISO 9001 y sedes en Buenos Aires, Argentina y Santiago de Chile.

Desde C&S estamos buscando candidatos/as para llenar distintas posiciones de M365.

Modalidad de trabajo

• Esquema remoto para candidatos del interior, para candidatos de AMBA híbrido con asistencia en oficinas en Parque Patricios.
• Horario de 9 a 18 horas.

• Conocimiento general de Microsoft 365 (SharePoint Online, MS Teams, Grupos de M365, etc.)
• Experiencia con herramientas de migración de M365
• Excelentes habilidades de comunicación y nivel de inglés avanzado (C1)
• Conocimientos de scripting en PowerShell (Deseable)

• Conocimiento general de Microsoft 365 (M365)
• Conocimientos avanzados como Administrador de SharePoint Online, con experiencia práctica
• Experiencia avanzada en resolución de problemas (troubleshooting)
• Excelentes habilidades de comunicación y nivel de inglés avanzado (C1)

• Experiencia: Preferentemente al menos 3 años trabajando con servicios de M365 y scripting en PowerShell.
• Experiencia comprobada en el desarrollo de aplicaciones y automatizaciones dentro de Power Platform.
• Excelentes habilidades de comunicación y nivel de inglés avanzado (C1)

• Dominio de la plataforma Microsoft Fabric y su administración.
• 4 años de experiencia en Microsoft 365.
• Excelentes habilidades de comunicación y nivel de inglés avanzado (C1)
• Dominio en la administración de Microsoft Power BI (Deseable)
• Experiencia con servicios de datos de Azure y herramientas relacionadas para integración y almacenamiento de datos (Deseable)
  

• Sólido entendimiento y conocimiento del soporte de aplicaciones M365.
• Dominio de los principios y prácticas de gestión de proyectos.
• Excelentes habilidades de comunicación y nivel de inglés avanzado (C1)

• Cobertura médica (Redirección de aporte)
• Revisiones cuatrimestrales de sueldo.
• Descuentos en universidades, centros educativos, y más.
• Bono de cumpleaños.
• Bono para internet y gastos del hogar.
• Equipo para que puedas trabajar desde tu casa.
• Kit de bienvenida al ingresar.

Overview

Software Development Engineer IBM Informix – Empleos IT

Autonomous City of Buenos Aires, Buenos Aires Province, Argentina

1 month ago Be among the first 25 applicants

Acerca de C&S
Somos una empresa de más de 160 profesionales, consolidada hace 38 años en el mercado. Nuestro propósito es garantizar la satisfacción de nuestros clientes; para ello, ofrecemos servicios de Desarrollo de Software, Talent Outsourcing y Consultoría IT. Contamos con certificación ISO 9001 y sedes en Buenos Aires, Argentina y Santiago de Chile.

Desde C&S estamos buscando candidatos/as para llenar distintas posiciones de M365.

• Esquema remoto para candidatos del interior, para candidatos de AMBA híbrido con asistencia en oficinas en Parque Patricios.
• Horario de 9 a 18 horas.

Ingeniero de migración de Datos en M365

• Conocimiento general de Microsoft 365 (SharePoint Online, MS Teams, Grupos de M365, etc.)
• Experiencia con herramientas de migración de M365
• Excelentes habilidades de comunicación y nivel de inglés avanzado (C1)
• Conocimientos de scripting en PowerShell (Deseable)

Ingeniero Sharepoint Online

• Conocimiento general de Microsoft 365 (M365)
• Conocimientos avanzados como Administrador de SharePoint Online, con experiencia práctica
• Experiencia avanzada en resolución de problemas (troubleshooting)
• Excelentes habilidades de comunicación y nivel de inglés avanzado (C1)

Desarrollador Powershell

• Experiencia: Preferentemente al menos 3 años trabajando con servicios de M365 y scripting en PowerShell.
• Experiencia comprobada en el desarrollo de aplicaciones y automatizaciones dentro de Power Platform.
• Excelentes habilidades de comunicación y nivel de inglés avanzado (C1)

Power BI/Fabric Engineer

• Dominio de la plataforma Microsoft Fabric y su administración.
• 4 años de experiencia en Microsoft 365.
• Excelentes habilidades de comunicación y nivel de inglés avanzado (C1)
• Dominio en la administración de Microsoft Power BI (Deseable)
• Experiencia con servicios de datos de Azure y herramientas relacionadas para integración y almacenamiento de datos (Deseable)

MS Teams Engineer

• Sólido entendimiento y conocimiento del soporte de aplicaciones M365.
• Dominio de los principios y prácticas de gestión de proyectos.
• Excelentes habilidades de comunicación y nivel de inglés avanzado (C1)

• Cobertura médica (Redirección de aporte)
• Revisiones cuatrimestrales de sueldo.
• Descuentos en universidades, centros educativos, y más.
• Bono de cumpleaños.
• Bono para internet y gastos del hogar.
• Equipo para que puedas trabajar desde tu casa.
• Kit de bienvenida al ingresar.

• Mid-Senior level

• Full-time

• Engineering and Information Technology
• Industries: Human Resources Services

Referrals increase your chances of interviewing at Empleos IT by 2x

Sign in to set job alerts for “Software Engineer” roles. Autonomous City of Buenos Aires, Buenos Aires Province, Argentina 5 days ago

SUMATE A NUESTRA BASE DE TALENTO SAP ARG

Autonomous City of Buenos Aires, Buenos Aires Province, Argentina 1 year ago

We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.

Overview

We are seeking a skilled AI Engineer with hands-on experience in Retrieval-Augmented Generation (RAG) to join our growing team. You will be responsible for building intelligent, context-aware AI systems that integrate LLMs with retrieval mechanisms to deliver accurate, explainable, and scalable solutions across real-world applications.

This role will be pivotal in shaping how we design, implement, and deploy production-grade AI systems that blend cutting-edge NLP techniques with robust data infrastructure.

• Design, implement, and deploy RAG pipelines using LLMs (e.g., OpenAI GPT, Claude, LLaMA, etc.) combined with vector stores or traditional search systems.
• Build and fine-tune retrievers (dense/sparse), embeddings, and index management using tools like FAISS , Weaviate , Pinecone , Elasticsearch , or Milvus .
• Develop context-aware applications by integrating structured/unstructured data into LLM prompting pipelines.
• Optimize LLM usage for latency , accuracy , cost-efficiency , and context window limitations .
• Collaborate with ML researchers, data engineers, and backend teams to integrate RAG-based solutions into production.
• Evaluate and compare different LLM models and retrieval strategies for specific business use cases.
• Monitor, evaluate, and iterate on deployed RAG systems using feedback loops and evaluation metrics.

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field.
• 5+ years of experience in AI/ML engineering, with at least 1–2 years working directly with RAG architectures .
• Strong knowledge of LLMs , embeddings , and retrieval systems .
• Proficiency in Python , and frameworks such as LangChain , LlamaIndex , or Haystack .
• Experience with vector databases (FAISS , Pinecone , Weaviate , etc.) and LLM APIs (OpenAI, Cohere, Anthropic, etc.).
• Familiarity with NLP tasks such as question answering, summarization, document retrieval, and semantic search.
• Ability to write clean, scalable, and maintainable code.
• Solid understanding of MLOps practices, versioning, and CI/CD for ML models.

• Seniority level : Mid-Senior level
• Employment type : Full-time
• Location : Remote - Argentina or any country in Latin America
• Job function : Information Technology and Engineering
• Industries : IT Services and IT Consulting and Software Development

Overview

We are seeking a skilled AI Engineer with hands-on experience in Retrieval-Augmented Generation (RAG) to join our growing team. You will be responsible for building intelligent, context-aware AI systems that integrate LLMs with retrieval mechanisms to deliver accurate, explainable, and scalable solutions across real-world applications.

This role will be pivotal in shaping how we design, implement, and deploy production-grade AI systems that blend cutting-edge NLP techniques with robust data infrastructure.

• Design, implement, and deploy RAG pipelines using LLMs (e.g., OpenAI GPT, Claude, LLaMA, etc.) combined with vector stores or traditional search systems.
• Build and fine-tune retrievers (dense/sparse), embeddings, and index management using tools like FAISS , Weaviate , Pinecone , Elasticsearch , or Milvus .
• Develop context-aware applications by integrating structured/unstructured data into LLM prompting pipelines.
• Optimize LLM usage for latency , accuracy , cost-efficiency , and context window limitations .
• Collaborate with ML researchers, data engineers, and backend teams to integrate RAG-based solutions into production.
• Evaluate and compare different LLM models and retrieval strategies for specific business use cases.
• Monitor, evaluate, and iterate on deployed RAG systems using feedback loops and evaluation metrics.

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field.
• 5+ years of experience in AI/ML engineering, with at least 1–2 years working directly with RAG architectures .
• Strong knowledge of LLMs , embeddings , and retrieval systems .
• Proficiency in Python , and frameworks such as LangChain , LlamaIndex , or Haystack .
• Experience with vector databases (FAISS , Pinecone , Weaviate , etc.) and LLM APIs (OpenAI, Cohere, Anthropic, etc.).
• Familiarity with NLP tasks such as question answering, summarization, document retrieval, and semantic search.
• Ability to write clean, scalable, and maintainable code.
• Solid understanding of MLOps practices, versioning, and CI/CD for ML models.

• Seniority level : Mid-Senior level
• Employment type : Full-time
• Location : Remote - Argentina or any country in Latin America
• Job function : Information Technology and Engineering
• Industries : IT Services and IT Consulting and Software Development

Overview

We are seeking a skilled AI Engineer with hands-on experience in Retrieval-Augmented Generation (RAG) to join our growing team. You will be responsible for building intelligent, context-aware AI systems that integrate LLMs with retrieval mechanisms to deliver accurate, explainable, and scalable solutions across real-world applications.

This role will be pivotal in shaping how we design, implement, and deploy production-grade AI systems that blend cutting-edge NLP techniques with robust data infrastructure.

• Design, implement, and deploy RAG pipelines using LLMs (e.g., OpenAI GPT, Claude, LLaMA, etc.) combined with vector stores or traditional search systems.
• Build and fine-tune retrievers (dense/sparse), embeddings, and index management using tools like FAISS , Weaviate , Pinecone , Elasticsearch , or Milvus .
• Develop context-aware applications by integrating structured/unstructured data into LLM prompting pipelines.
• Optimize LLM usage for latency , accuracy , cost-efficiency , and context window limitations .
• Collaborate with ML researchers, data engineers, and backend teams to integrate RAG-based solutions into production.
• Evaluate and compare different LLM models and retrieval strategies for specific business use cases.
• Monitor, evaluate, and iterate on deployed RAG systems using feedback loops and evaluation metrics.

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field.
• 5+ years of experience in AI/ML engineering, with at least 1–2 years working directly with RAG architectures .
• Strong knowledge of LLMs , embeddings , and retrieval systems .
• Proficiency in Python , and frameworks such as LangChain , LlamaIndex , or Haystack .
• Experience with vector databases (FAISS , Pinecone , Weaviate , etc.) and LLM APIs (OpenAI, Cohere, Anthropic, etc.).
• Familiarity with NLP tasks such as question answering, summarization, document retrieval, and semantic search.
• Ability to write clean, scalable, and maintainable code.
• Solid understanding of MLOps practices, versioning, and CI/CD for ML models.

• Seniority level : Mid-Senior level
• Employment type : Full-time
• Location : Remote - Argentina or any country in Latin America
• Job function : Information Technology and Engineering
• Industries : IT Services and IT Consulting and Software Development

Overview

We are seeking a skilled AI Engineer with hands-on experience in Retrieval-Augmented Generation (RAG) to join our growing team. You will be responsible for building intelligent, context-aware AI systems that integrate LLMs with retrieval mechanisms to deliver accurate, explainable, and scalable solutions across real-world applications.

This role will be pivotal in shaping how we design, implement, and deploy production-grade AI systems that blend cutting-edge NLP techniques with robust data infrastructure.

• Design, implement, and deploy RAG pipelines using LLMs (e.g., OpenAI GPT, Claude, LLaMA, etc.) combined with vector stores or traditional search systems.
• Build and fine-tune retrievers (dense/sparse), embeddings, and index management using tools like FAISS , Weaviate , Pinecone , Elasticsearch , or Milvus .
• Develop context-aware applications by integrating structured/unstructured data into LLM prompting pipelines.
• Optimize LLM usage for latency , accuracy , cost-efficiency , and context window limitations .
• Collaborate with ML researchers, data engineers, and backend teams to integrate RAG-based solutions into production.
• Evaluate and compare different LLM models and retrieval strategies for specific business use cases.
• Monitor, evaluate, and iterate on deployed RAG systems using feedback loops and evaluation metrics.

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field.
• 5+ years of experience in AI/ML engineering, with at least 1–2 years working directly with RAG architectures .
• Strong knowledge of LLMs , embeddings , and retrieval systems .
• Proficiency in Python , and frameworks such as LangChain , LlamaIndex , or Haystack .
• Experience with vector databases (FAISS , Pinecone , Weaviate , etc.) and LLM APIs (OpenAI, Cohere, Anthropic, etc.).
• Familiarity with NLP tasks such as question answering, summarization, document retrieval, and semantic search.
• Ability to write clean, scalable, and maintainable code.
• Solid understanding of MLOps practices, versioning, and CI/CD for ML models.

• Seniority level : Mid-Senior level
• Employment type : Full-time
• Location : Remote - Argentina or any country in Latin America
• Job function : Information Technology and Engineering
• Industries : IT Services and IT Consulting and Software Development

Overview

We are seeking a skilled AI Engineer with hands-on experience in Retrieval-Augmented Generation (RAG) to join our growing team. You will be responsible for building intelligent, context-aware AI systems that integrate LLMs with retrieval mechanisms to deliver accurate, explainable, and scalable solutions across real-world applications.

This role will be pivotal in shaping how we design, implement, and deploy production-grade AI systems that blend cutting-edge NLP techniques with robust data infrastructure.

• Design, implement, and deploy RAG pipelines using LLMs (e.g., OpenAI GPT, Claude, LLaMA, etc.) combined with vector stores or traditional search systems.
• Build and fine-tune retrievers (dense/sparse), embeddings, and index management using tools like FAISS , Weaviate , Pinecone , Elasticsearch , or Milvus .
• Develop context-aware applications by integrating structured/unstructured data into LLM prompting pipelines.
• Optimize LLM usage for latency , accuracy , cost-efficiency , and context window limitations .
• Collaborate with ML researchers, data engineers, and backend teams to integrate RAG-based solutions into production.
• Evaluate and compare different LLM models and retrieval strategies for specific business use cases.
• Monitor, evaluate, and iterate on deployed RAG systems using feedback loops and evaluation metrics.

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field.
• 5+ years of experience in AI/ML engineering, with at least 1–2 years working directly with RAG architectures .
• Strong knowledge of LLMs , embeddings , and retrieval systems .
• Proficiency in Python , and frameworks such as LangChain , LlamaIndex , or Haystack .
• Experience with vector databases (FAISS , Pinecone , Weaviate , etc.) and LLM APIs (OpenAI, Cohere, Anthropic, etc.).
• Familiarity with NLP tasks such as question answering, summarization, document retrieval, and semantic search.
• Ability to write clean, scalable, and maintainable code.
• Solid understanding of MLOps practices, versioning, and CI/CD for ML models.

• Seniority level : Mid-Senior level
• Employment type : Full-time
• Location : Remote - Argentina or any country in Latin America
• Job function : Information Technology and Engineering
• Industries : IT Services and IT Consulting and Software Development

Overview

We are seeking a skilled AI Engineer with hands-on experience in Retrieval-Augmented Generation (RAG) to join our growing team. You will be responsible for building intelligent, context-aware AI systems that integrate LLMs with retrieval mechanisms to deliver accurate, explainable, and scalable solutions across real-world applications.

This role will be pivotal in shaping how we design, implement, and deploy production-grade AI systems that blend cutting-edge NLP techniques with robust data infrastructure.

• Design, implement, and deploy RAG pipelines using LLMs (e.g., OpenAI GPT, Claude, LLaMA, etc.) combined with vector stores or traditional search systems.
• Build and fine-tune retrievers (dense/sparse), embeddings, and index management using tools like FAISS , Weaviate , Pinecone , Elasticsearch , or Milvus .
• Develop context-aware applications by integrating structured/unstructured data into LLM prompting pipelines.
• Optimize LLM usage for latency , accuracy , cost-efficiency , and context window limitations .
• Collaborate with ML researchers, data engineers, and backend teams to integrate RAG-based solutions into production.
• Evaluate and compare different LLM models and retrieval strategies for specific business use cases.
• Monitor, evaluate, and iterate on deployed RAG systems using feedback loops and evaluation metrics.

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field.
• 5+ years of experience in AI/ML engineering, with at least 1–2 years working directly with RAG architectures .
• Strong knowledge of LLMs , embeddings , and retrieval systems .
• Proficiency in Python , and frameworks such as LangChain , LlamaIndex , or Haystack .
• Experience with vector databases (FAISS , Pinecone , Weaviate , etc.) and LLM APIs (OpenAI, Cohere, Anthropic, etc.).
• Familiarity with NLP tasks such as question answering, summarization, document retrieval, and semantic search.
• Ability to write clean, scalable, and maintainable code.
• Solid understanding of MLOps practices, versioning, and CI/CD for ML models.

• Seniority level : Mid-Senior level
• Employment type : Full-time
• Location : Remote - Argentina or any country in Latin America
• Job function : Information Technology and Engineering
• Industries : IT Services and IT Consulting and Software Development

Overview

We are seeking a skilled AI Engineer with hands-on experience in Retrieval-Augmented Generation (RAG) to join our growing team. You will be responsible for building intelligent, context-aware AI systems that integrate LLMs with retrieval mechanisms to deliver accurate, explainable, and scalable solutions across real-world applications.

This role will be pivotal in shaping how we design, implement, and deploy production-grade AI systems that blend cutting-edge NLP techniques with robust data infrastructure.

• Design, implement, and deploy RAG pipelines using LLMs (e.g., OpenAI GPT, Claude, LLaMA, etc.) combined with vector stores or traditional search systems.
• Build and fine-tune retrievers (dense/sparse), embeddings, and index management using tools like FAISS , Weaviate , Pinecone , Elasticsearch , or Milvus .
• Develop context-aware applications by integrating structured/unstructured data into LLM prompting pipelines.
• Optimize LLM usage for latency , accuracy , cost-efficiency , and context window limitations .
• Collaborate with ML researchers, data engineers, and backend teams to integrate RAG-based solutions into production.
• Evaluate and compare different LLM models and retrieval strategies for specific business use cases.
• Monitor, evaluate, and iterate on deployed RAG systems using feedback loops and evaluation metrics.

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field.
• 5+ years of experience in AI/ML engineering, with at least 1–2 years working directly with RAG architectures .
• Strong knowledge of LLMs , embeddings , and retrieval systems .
• Proficiency in Python , and frameworks such as LangChain , LlamaIndex , or Haystack .
• Experience with vector databases (FAISS , Pinecone , Weaviate , etc.) and LLM APIs (OpenAI, Cohere, Anthropic, etc.).
• Familiarity with NLP tasks such as question answering, summarization, document retrieval, and semantic search.
• Ability to write clean, scalable, and maintainable code.
• Solid understanding of MLOps practices, versioning, and CI/CD for ML models.

• Seniority level : Mid-Senior level
• Employment type : Full-time
• Location : Remote - Argentina or any country in Latin America
• Job function : Information Technology and Engineering
• Industries : IT Services and IT Consulting and Software Development