Build pipelines for processing business-critical documents such as contracts, invoices, forms, statements, claims, and enterprise records.
Optimize document understanding workflows to improve accuracy, automation, and scalability.
Collaborate with business and technical teams to identify opportunities for document intelligence automation.
Agentic AI Solutions
Design and implement Agentic AI architectures capable of autonomous reasoning and task execution.
Develop AI agents leveraging
Tool Calling
Function Calling
Multi-Agent Architectures
Agent Orchestration
Planning Frameworks
Human-in-the-Loop Workflows
Long-Term Context and Memory Management
Define governance and operational controls for enterprise AI agents.
Implement monitoring and quality controls for agent behavior and decision-making.
Generative AI & RAG Engineering
Build production-ready LLM and Retrieval-Augmented Generation (RAG) solutions.
Develop retrieval pipelines using
Embeddings
Vector Databases
Semantic Search
Knowledge Bases
Grounding Frameworks
Design and optimize prompt engineering strategies.
Implement evaluation frameworks to improve model accuracy, reliability, and relevance.
Support enterprise knowledge management and AI-powered search experiences.
Cloud AI Platform Engineering
Design, deploy, and support AI solutions within cloud environments.
Leverage Google Cloud Platform (GCP) AI and Machine Learning services when applicable.
Collaborate with Cloud and Data Engineering teams to build scalable AI architectures.
Define deployment patterns, scalability strategies, and operational support models for AI applications.
Support MLOps and AI lifecycle management activities.
Software Engineering & Platform Development
Develop scalable AI applications using Python and modern software engineering practices.
Build APIs, services, and integration layers supporting AI-powered capabilities.
Implement observability, monitoring, logging, and performance optimization solutions.
Ensure solutions meet enterprise requirements for security, reliability, and maintainability.
Contribute to architecture reviews, technical standards, and AI engineering best practices.
Your Profile
AI innovator – Passionate about emerging technologies and intelligent automation.
Hands-on engineer – Comfortable building and deploying enterprise-grade solutions.
Problem solver – Excels at translating complex business challenges into scalable AI solutions.
Architectural thinker – Understands how AI solutions fit within broader enterprise ecosystems.
Collaborative professional – Works effectively with business stakeholders, engineers, and architects.
Continuous learner – Stays current with advancements in AI, GenAI, Agentic systems, and cloud technologies.
Qualifications & Preferred Skills
Required Skills
Document AI & OCR
Strong hands-on experience with OCR and Intelligent Document Processing solutions.
Demonstrated experience extracting, classifying, validating, and processing information from unstructured documents.
Experience implementing enterprise Document AI workflows and document understanding capabilities.
Agentic AI
Proven experience designing and implementing Agentic AI systems.
Experience with
AI Agents
Multi-Agent Architectures
Agent Orchestration
Planning Systems
Memory Management
Tool and Function Calling
Human-in-the-Loop Workflows
Ability to design autonomous workflows beyond traditional LLM implementations.
LLMs & RAG
Strong expertise in
Large Language Models (LLMs)
Prompt Engineering
Retrieval-Augmented Generation (RAG)
Embeddings
Vector Databases
Semantic Retrieval
Grounding Strategies
Experience building and deploying production-grade RAG solutions.
Knowledge of model evaluation and optimization techniques.
Software Engineering
Strong Python development experience.
Experience designing and developing APIs and backend services.
Knowledge of software engineering best practices and enterprise application development.
Ability to build scalable, maintainable, and production-ready solutions.
Production AI Engineering
Experience taking AI solutions through the complete lifecycle
Proof of Concept (POC)
Architecture Design
Development
Deployment
Monitoring
Optimization
Scaling
Strong understanding of enterprise operational requirements for AI systems.
Preferred Skills
Experience with Google Cloud Platform (GCP).
Hands-on experience with
Vertex AI
Gemini
Document AI
Cloud Run
GKE
BigQuery
Experience with Azure OpenAI or AWS AI/ML services.
Familiarity with MLOps and AI Ops frameworks.
Knowledge of data engineering and analytics ecosystems.
Experience implementing enterprise AI governance and responsible AI practices.
Exposure to data security, compliance, and privacy requirements.
What You'll Love
Opportunity to work at the intersection of Product Management, Data, Analytics, and Marketing Technology.
Exposure to enterprise-scale digital transformation initiatives.
Collaboration with global Product, Engineering, Analytics, and Business teams.
Access to certifications, learning programs, mentorship, and professional development opportunities.
Innovative and collaborative work environment focused on continuous improvement.
Career growth opportunities within Capgemini's Digital, Data, and Product Management practices.
Need to Know
Career Development in Spanish & English: Access to certifications, product management training, Agile academies, mentorship programs, and continuous learning opportunities.
Community Engagement: Participate in innovation challenges, product communities, knowledge-sharing sessions, volunteering programs, and networking 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, customer experience, 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
574757
Posted on
Nov 11, 2026
Experience Level
Experienced Professionals
Contract Type
Permanent
Location
Aguascalientes, MX
Brand
Capgemini
Professional Community
Data & AI
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