Job Summary

We are seeking an experienced Senior AI Architect to lead the design, development, and implementation of enterprise-scale Artificial Intelligence (AI) and Generative AI solutions. This role is responsible for defining AI strategy, architecting scalable machine learning platforms, governing AI best practices, and collaborating with business and technology leaders to deliver innovative, secure, and production-ready AI capabilities.

The idóneo candidate possesses deep expertise in AI/ML architectures, Large Language Models (LLMs), cloud platforms, MLOps, data engineering, and enterprise integration patterns. The Senior AI Architect will serve as a trusted advisor, technical leader, and mentor while driving AI adoption across the organization.

Key Responsibilities

AI Strategy & Architecture

- Define and maintain enterprise AI architecture standards, frameworks, and best practices.
- Design and develop end-to-end AI, Machine Learning, and Generative AI solutions aligned with business objectives.
- Create scalable architectures for predictive analytics, recommendation systems, intelligent automation, and conversational AI.
- Evaluate emerging AI technologies, frameworks, and vendor solutions to drive innovation.
- Lead AI roadmap development and technology modernization initiatives.

Generative AI & LLM Solutions
- Architect and deploy Generative AI solutions using Large Language Models (LLMs).
- Design Retrieval-Augmented Generation (RAG) architectures and knowledge-based AI systems.
- Implement prompt engineering, agent-based systems, vector databases, and AI orchestration frameworks.
- Develop governance frameworks for responsible AI, explainability, bias mitigation, and security.
- Optimize AI model performance, scalability, and cost efficiency.

Cloud & Platform Engineering
- Design AI platforms leveraging cloud services such as Azure, AWS,



or Google Cloud.
- Establish AI infrastructure standards including model deployment, monitoring, and lifecycle management.
- Build scalable MLOps capabilities for continuous integration, testing, deployment, and monitoring.
- Implement AI observability, model governance, and performance management practices.

Leadership & Stakeholder Engagement
- Partner with executives, business leaders, product teams, and engineering organizations to identify AI opportunities.
- Provide technical leadership to data scientists, machine learning engineers, data engineers, and software developers.
- Lead architecture reviews, technical design discussions, and AI governance boards.
- Mentor teams and promote AI best practices throughout the organization.

Security & Compliance
- Ensure AI solutions comply with security, privacy, regulatory, and governance requirements.
- Develop secure AI architecture patterns for handling sensitive data.
- Collaborate with security and compliance teams to mitigate risks associated with AI deployment.
- Establish responsible AI policies and controls.

Required Qualifications
- Bachelor's degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, or a related field.
- 10+ years of experience in software engineering, data engineering, cloud architecture, or enterprise architecture.
- 5+ years of experience designing and implementing AI and Machine Learning solutions.




- Hands-on experience with Generative AI technologies, LLMs, and AI orchestration frameworks.
- Strong expertise in AI architecture patterns, machine learning lifecycle management, and MLOps practices.
- Experience with enterprise integration, APIs, microservices, and distributed systems.
- Proficiency with Python and modern AI/ML development frameworks.
- Strong communication, leadership, and stakeholder management skills.

Preferred Qualifications
- Master's or PhD in Artificial Intelligence, Computer Science, Data Science, or related discipline.
- Experience with Microsoft Azure AI, Azure OpenAI, AWS AI/ML, or Google Vertex AI.
- Experience implementing enterprise-scale RAG architectures and AI assistants.
- Knowledge of Responsible AI, AI governance, and ethical AI frameworks.
- Experience with Kubernetes, Docker, Infrastructure as Code (Terraform), and DevOps practices.
- AI, cloud, or enterprise architecture certifications.

Required Technical Skills AI & Machine Learning
- Machine Learning
- Deep Learning
- Natural Language Processing (NLP)
- Computer Vision
- Predictive Analytics
- Reinforcement Learning
- Feature Engineering
- Model Evaluation & Optimization

Generative AI
- OpenAI / Azure OpenAI
- LLM Architecture
- Prompt Engineering
- RAG (Retrieval-Augmented Generation)
- AI Agents
- LangChain
- Semantic Kernel
- Vector Databases
- Model Fine-Tuning

MLOps & Data Engineering
- MLflow
- Kubeflow
- Data Pipelines
- Model Monitoring
- Feature Stores
- Apache Spark
- Databricks
- Airflow

Cloud Platforms
- Microsoft Azure
- Amazon Web Services (AWS)
- Google Cloud Platform (GCP)

Programming Languages
- Python
- SQL
- Java
- Scala
- JavaScript (preferred)

DevOps & Infrastructure
- Kubernetes
- Docker
- Terraform
- GitHub Actions
- Azure DevOps
- Jenkins

📌 Senior AI Architect (Guadalajara)
🏢 Brillio
📍 Guadalajara