Build scalable feature engineering, training, validation, and inference pipelines.
Develop production-ready model services, APIs, and AI-enabled application components.
Implement model monitoring, performance tracking, and continuous improvement processes.
Ensure reliability, scalability, and maintainability of ML solutions in production environments.
Generative AI & LLM Solutions
Design and implement enterprise Generative AI solutions leveraging Large Language Models (LLMs).
Develop prompt engineering strategies and model optimization approaches.
Build Retrieval-Augmented Generation (RAG) architectures for knowledge retrieval and intelligent search.
Implement vector search solutions leveraging embeddings and vector databases.
Evaluate and optimize AI solutions using established AI evaluation methodologies and benchmarks.
Support customization and fine-tuning of foundation models.
Agentic AI & Multi-Agent Systems
Design and develop Agentic AI solutions utilizing
LangChain
LangGraph
Multi-Agent Architectures
Agent Orchestration Frameworks
Tool Calling
Workflow Automation
Build intelligent autonomous workflows that leverage reasoning, planning, memory, and external tools.
Implement secure and scalable AI agent frameworks aligned with enterprise requirements.
Data Engineering & AI Pipelines
Develop robust data preparation and feature engineering pipelines.
Design end-to-end ML workflows supporting
Data Ingestion
Feature Creation
Model Training
Evaluation
Deployment
Monitoring
Collaborate with data engineering teams to support scalable AI and analytics platforms.
Ensure data quality, lineage, and reproducibility across AI initiatives.
Cloud AI & MLOps
Deploy and manage AI workloads within Google Cloud Platform or similar cloud environments.
Implement MLOps practices and automation pipelines.
Design CI/CD workflows supporting machine learning lifecycle management.
Develop scalable model serving architectures and inference endpoints.
Support containerized and cloud-native AI deployments.
Collaboration & Innovation
Partner with Product Owners and Business Stakeholders to translate business objectives into measurable AI use cases.
Define acceptance criteria, success metrics, and performance objectives for AI solutions.
Participate in architecture discussions, technical design reviews, and innovation initiatives.
Mentor team members and contribute to AI engineering best practices.
Your Profile
AI innovator – Passionate about Machine Learning, Generative AI, and emerging technologies.
Hands-on builder – Enjoys designing and developing production-grade AI solutions.
Problem solver – Able to simplify complex challenges through data-driven approaches.
Cloud-native engineer – Comfortable building scalable solutions in modern cloud environments.
Collaborative professional – Thrives in cross-functional teams and agile environments.
Continuous learner – Stays current with advancements in AI, ML, MLOps, and GenAI technologies.
Qualifications & Preferred Skills
Required Skills
Machine Learning & Deep Learning
Strong expertise in Machine Learning and Deep Learning techniques.
Experience building production-grade predictive models and AI solutions.
Solid understanding of
Supervised Learning
Unsupervised Learning
Deep Learning
Natural Language Processing (NLP)
Transformers Architecture
Generative AI & RAG
Hands-on experience with
Large Language Models (LLMs)
Retrieval-Augmented Generation (RAG)
Embeddings
Vector Databases
Semantic Search
Hybrid Search
Prompt Engineering
Experience implementing end-to-end RAG pipelines.
Knowledge of AI evaluation methodologies and model benchmarking.
Agentic AI
Experience designing and implementing Agentic AI systems.
Hands-on experience with
LangChain
LangGraph
Multi-Agent Architectures
Agent Orchestration Frameworks
Tool Integration
Workflow Automation
Programming & Frameworks
Advanced proficiency in
Python
SQL
Hands-on experience with
TensorFlow
PyTorch
JAX
Strong software engineering and API development capabilities.
Cloud & Deployment
Experience deploying AI/ML solutions on
Google Cloud Platform (preferred)
Azure
AWS
Experience with production deployment, scaling, and operational support of AI systems.
Preferred Skills
Google Cloud & Vertex AI
Experience leveraging
Vertex AI
Vertex AI Pipelines
Vertex AI Workbench
Model Registry
Feature Store
Vertex AI Studio
Experience customizing and deploying Gemini-based solutions.
Data Engineering & Analytics
BigQuery
BigQuery ML
Cloud Storage
Dataflow
Apache Beam
Dataproc
Enterprise Data Pipelines
MLOps & Platform Engineering
Kubeflow
Cloud Composer (Airflow)
CI/CD for ML
Containerization (Docker)
Kubernetes (GKE)
Cloud Run
Automated Model Deployment
Model Operations
Model Monitoring
Feature Drift Detection
Data Drift Analysis
Latency Monitoring
Model Performance Optimization
AI Governance and Responsible AI Practices
What You'll Love
Opportunity to work on cutting-edge AI, Machine Learning, and Generative AI initiatives.
Exposure to enterprise-scale AI transformation programs and emerging technologies.
Access to Google Cloud AI, Vertex AI, Gemini, and advanced ML platforms.
Collaboration with global Data, AI, Analytics, and Cloud experts.
Continuous learning through certifications, technical academies, mentoring, and innovation programs.
Career growth opportunities within Capgemini's Global Data & AI practice.
Need to Know
Career Development in Spanish & English: Access to AI, Machine Learning, Cloud, and Data Engineering certifications, mentorship programs, technical academies, and continuous learning opportunities.
Community Engagement: Participate in AI communities, innovation labs, hackathons, knowledge-sharing forums, technical events, and volunteering initiatives across Capgemini.
About Capgemini
Capgemini is a global business and technology transformation partner, helping organizations accelerate their dual transition to a digital and sustainable world while creating tangible impact for enterprises and society. It is a responsible and diverse organization with more than 340,000 team members in over 50 countries.
With a strong heritage of more than 55 years, Capgemini helps clients unlock the value of technology through end-to-end services and solutions, leveraging capabilities in strategy and design, engineering, AI, generative AI, cloud, data, and digital transformation.
At Capgemini Mexico, we are committed to fostering a diverse and inclusive workplace where everyone has equal opportunities. We welcome applications from all qualified candidates and evaluate them based on merit, skills, qualifications, and experience relevant to the role.
Ref. code
589474
Posted on
Nov 3, 2026
Experience Level
Experienced Professionals
Contract Type
Permanent
Location
Aguascalientes, MX
Brand
Capgemini
Professional Community
Data & AI
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