Required Technical Skills

- Cloud:

AWS, including services for compute, storage, databases, security, monitoring, and AI/ML

- Programming:

Python, SQL, scripting, and API development

- Data Platforms:

Relational databases, NoSQL, data lakes, data warehouses, and vector databases

- Data Integration:

ETL/ELT, REST APIs, event streaming, messaging, and microservices

- AI:

Generative AI, AI agents, RAG, prompt orchestration, embeddings, model evaluation, and responsible AI controls

- Computer Vision:

OpenCV, image preprocessing, classification, object detection, OCR, model evaluation, and inference pipelines

- DevOps:

Git, automated testing, CI/CD, infrastructure as code, release management, and environment management

- Containers:

Docker and Kubernetes or equivalent container platforms

- Security:

Secure coding, vulnerability scanning, secrets management, IAM, encryption, audit logging, and compliance

- Monitoring:

Application, database, pipeline, infrastructure, and AI-model observability

Preferred Qualifications

- Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.

- Experience in manufacturing, automotive, engineering, industrial,



or product-development environments.

- Experience with AWS services such as S3, RDS, Redshift, Glue, Lambda, API Gateway, SageMaker, Bedrock, IAM, CloudWatch, and EKS.

- Experience with knowledge graphs, enterprise search, vector databases, or semantic data models.

- Experience with MLOps platforms and model lifecycle management.

- Experience deploying AI or computer vision solutions at the edge.

- Familiarity with data-governance frameworks, model-risk management, and responsible AI principles.

- AWS, data architecture, security, Kubernetes, or AI/ML certifications.

- Experience leading proof-of-concept efforts and transitioning them into supported production solutions.

Key Competencies

- Enterprise and systems thinking

- Hands-on technical leadership

- Data and AI governance

- Security-by-design

- Architecture decision-making

- Problem-solving and root-cause analysis

- Stakeholder alignment

- Technical documentation

- Project prioritization and roadmap development

- Ability to balance innovation, security, scalability, cost, and operational sustainability

📌 Data Architect (México)
🏢 Pyramid Consulting
📍 México