2 publicaciones de empleo destacadas en software engineer – automation & observability (¡Están contratando!)

AI Engineer (Remote in México)
Capgemini Sogeti —Aguascalientes, Ags.
- Home Office (Desde casa)
- Azure
- DevOps
- Experiencia en bases de datos
6h
Senior Devops Engineer - AWS & Azure
Jalasoft —México
- Tiempo completo
- Home Office (Desde casa)
- Azure
- DevOps
- Java
Postulación rápida

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AI Engineer (Remote in México)

Capgemini Sogeti -
Aguascalientes, Ags.

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Información del empleo

Hace 6 horas

Cualificaciones

Modelos de inteligencia artificial
Azure
Kubernetes
DevOps
C#
NoSQL
.NET
Experiencia en bases de datos
SQL
Docker
Seguridad
Python

Descripción completa del empleo

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same.

Your role

Design, develop, implement, and operate enterprise-grade solutions based on Generative AI, Machine Learning, and Intelligent Automation on Microsoft Azure. This role is responsible for building scalable AI components, integrating foundation models and cognitive services with business applications, and ensuring the secure, efficient, and governed operation of AI solutions in production environments.

AI Solution Development

Design and implement applications powered by Generative AI and Large Language Models (LLMs).
Build enterprise copilots, virtual assistants, and intelligent agents.
Develop semantic search and Retrieval-Augmented Generation (RAG) solutions.
Implement reasoning, orchestration, and automation mechanisms through AI agents.
Integrate AI services with enterprise applications, APIs, and data platforms.

Data Engineering for AI

Design data ingestion, transformation, and enrichment pipelines.
Implement knowledge indexing and vectorization strategies.
Manage structured and unstructured knowledge repositories.
Ensure the quality, consistency, and traceability of data consumed by AI models.

Deployment and Operations

Deploy solutions using Azure managed services.
Implement LLMOps, MLOps, and DevSecOps practices.
Monitor solution performance, costs, accuracy, and adoption.
Manage prompt, model, and AI component versioning.

Quality and Security

Apply Responsible AI principles.
Implement security controls and data protection mechanisms.
Ensure compliance with enterprise and regulatory standards.
Participate in architecture and technical quality reviews.

Your profile

5+ years of professional experience. 2+ years implementing enterprise Generative AI solutions.
Hands-on experience developing Generative AI (GenAI) solutions in enterprise environments.
Practical experience with Azure OpenAI Service and Microsoft Azure AI services.
Experience designing and implementing Retrieval-Augmented Generation (RAG) solutions.
Proven experience building AI Agents, Copilots, and intelligent virtual assistants.
Strong programming skills in Python and/or C# (.NET).
Experience with AI orchestration frameworks such as Semantic Kernel, LangChain, LangGraph, CrewAI, or similar.
Experience integrating solutions through REST APIs and enterprise systems.
Knowledge of Azure AI Search, embeddings, and vector search technologies.
Experience working with SQL and NoSQL databases.
Ability to manage and leverage structured and unstructured data for AI applications.
Experience implementing LLMOps, MLOps, and DevOps practices.
Familiarity with Azure DevOps, GitHub Actions, and CI/CD pipelines.
Knowledge of Terraform, Bicep, or Infrastructure as Code (IaC).
Experience deploying, operating, and supporting AI solutions in production environments on Azure.
Understanding of observability, monitoring, security, Responsible AI, and AI governance.

Nice to Have

Experience with Azure Machine Learning.
Knowledge of Databricks and/or Microsoft Fabric.
Experience with model fine-tuning.
Experience building event-driven architectures.
Exposure to Multi-Agent Systems.
Experience with Docker, Kubernetes (AKS), or Azure Container Apps.
Microsoft certifications related to Azure AI, Development, or Cloud Architecture.
Certifications:
- Microsoft Certified: Azure AI Engineer Associate (AI-102)
- Microsoft Certified: Azure Developer Associate (AZ-204)
- Microsoft Certified: Azure Solutions Architect Expert (AZ-305)
- Microsoft Applied Skills – Azure OpenAI
- DP-100 Azure Data Scientist Associate
- Databricks Generative AI Fundamentals

What you will love

Empowered Careers with Purpose: Work on meaningful projects that use technology to solve real-world challenges. Be part of a company that values sustainability, inclusion, and digital equity. Contribute to building a better future for people, planet, and society.
Growth and Learning at Every Step: Access continuous learning through internal academies, certifications, and mentorship. Explore career mobility across roles, industries, and geographies. Be part of a “school of excellence” where your skills resonate beyond the company
Own your growth: Open access to digital learning platforms. Digital campuses on AI, Cloud, Data or Sustainability. Award winning career acceleration programs

Need to know

Work Modality Options: Choose between remote, hybrid, or on-site work depending on project needs and personal preferences. Offices available in CDMX, GDL, AGS.

About Capgemini

Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of over 420,000 team members in more than 50 countries. We deliver end-toend services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations.

At Capgemini Mexico, we aim to attract the best talent and are committed to creating a diverse and inclusive work environment, so there is no discrimination based on race, sex, sexual orientation, gender identity or expression, or any other characteristic of a person. All applications welcome and will be considered based on merit against the job and/or experience for the position.

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