Guest Tech - AI/ML Engineer (QA)
Capgemini Aguascalientes City, Aguascalientes, Mexico
IT Services and IT Consulting · 10,001+ employees
About the role
Develop and deploy scalable GenAI applications using LLMs, RAG architectures, and conversational AI platforms. Collaborate with cross-functional teams to optimize model performance, latency, and cost while integrating with cloud environments.
What they look for
Requirements
Requires strong programming skills in Python or Node.js and hands-on experience with LLMs, vector databases, and MLOps fundamentals. Candidates should have familiarity with conversational AI platforms and orchestration frameworks like LangChain.
Benefits
Full description
Capgemini
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
Your Role
- Looking for a Generative AI Engineer to build, integrate, and optimize AI solutions using Large Language Models (LLMs), RAG pipelines, conversational AI platforms, and modern AI orchestration frameworks.
- The role focuses on delivering scalable, production‑grade GenAI applications for enterprise use cases. Key Responsibilities Develop GenAI applications using LLMs, embeddings, and RAG architectures.
- Build and deploy chatbots, virtual assistants, and conversational workflows (Dialogflow CX, Copilot Studio). Implement AI workflows using LangChain, LangGraph, and vector databases.
- Optimize models for performance, latency, and cost; integrate with cloud platforms (Azure/AWS/GCP). Collaborate with product, engineering, and data teams to deliver reliable AI features.
Your Profile
- Required Skills Strong programming in Python or Node.js. Hands‑on experience with LLMs, RAG, embeddings, and vector databases.
- Experience with cloud deployment and MLOps fundamentals.
- Familiarity with conversational AI platforms (Dialogflow CX, GenAI playbooks). Preferred Skills Knowledge of multimodal models, agentic AI, and model fine‑tuning.
- Exposure to LangChain / LangGraph and orchestration frameworks.
What you’ll love
Empowered Careers with Purpose: Work on meaningful projects that use technology to solve real-world challenges.
Growth and Learning at Every Step: Access continuous learning through internal academies, certifications and mentorship.
Own your growth: Open access to digital learning platforms
About Capgemini
Capgemini (Footer)
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
Job Description
The role of a machine learning professional involves applying machine learning techniques and algorithms to solve complex problems, analyze data, and develop intelligent systems.
Job Description - Grade Specific
The role brings deep technical knowledge and expertise in machine learning to help clients or organizations navigate the complex landscape of AI. Plays a crucial role in providing designing solutions and ensuring successful implementation of machine learning projects to drive business impact. Also, assist in testing, deploying and monitoring models in production environments
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