Senior AI Engineer - Build Production-Grade GenAI Solutions

Capgemini Engineering; México; Remote; MXN 900.000 - 1.500.000; Vollzeit

Zusammenfassung

Capgemini Engineering is seeking a Sr AI Engineer to design, develop, and deploy scalable AI and Generative AI solutions that solve complex business problems. You will lead architecture discussions, mentor teams, and deliver production-ready applications using LLMs, RAG, and vector search technologies.

The role requires 6+ years in AI/ML or related fields, strong Python skills, and hands-on experience with Docker, Kubernetes, and cloud platforms such as Azure, AWS, or GCP.

Qualifikationen

• Bachelor degree in Computer Science or equivalent.
• 6+ years in AI, ML, data engineering, software engineering, or related roles.
• Proven experience deploying AI/ML or Generative AI solutions in production.
• Strong proficiency in Python and software development practices.
• Experience with AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn.
• Hands-on with LLMs, RAG, embeddings, and vector search technologies.

Aufgaben

• Design, develop, deploy, and maintain end-to-end AI and Generative AI solutions.
• Lead, mentor, and guide architecture discussions and deployment strategies.
• Build ML models, LLM apps, and RAG architectures for enterprise use.
• Develop scalable APIs, microservices, and backend services.
• Utilize cloud-native AI services to deliver production-grade solutions.
• Implement MLOps, CI/CD, monitoring, and model lifecycle management.
• Use vector databases and AI agent frameworks to enhance capabilities.
• Collaborate with data scientists, product managers, and stakeholders.

Kenntnisse

AI/ML expertise

Python

REST APIs

MLOps

Cloud platforms (Azure/AWS/GCP)

Distributed systems

Ausbildung

Bachelor's degree in Computer Science

Tools

Docker

Kubernetes

Vertex AI

TensorFlow

Jobbeschreibung

Capgemini Engineering is seeking a Sr AI Engineer to design, develop, and deploy scalable AI and Generative AI solutions that solve complex business problems. You will lead architecture discussions, mentor teams, and deliver production-ready applications using LLMs, RAG, and vector search technologies.

The role requires 6+ years in AI/ML or related fields, strong Python skills, and hands-on experience with Docker, Kubernetes, and cloud platforms such as Azure, AWS, or GCP.