To design scalable, secure, cloud-native SaaS applications that incorporate AI and data engineering technologies. Serve as a bridge between technical and business teams to define system architecture, cloud strategies, and intelligent, data-driven solutions in both English and Spanish environments
Key Responsabilities:
Design and architect secure, scalable, high-performance cloud-native SaaS applications
Lead technical discovery sessions with customers and internal stakeholders in both English and Spanish
Integrate AI/ML models into software products to enable intelligent automation and predictive features
Define data pipelines and architecture in collaboration with data engineering teams to support analytics and AI
Translate business requirements into technical specifications and end-to-end system designs
Provide architectural guidance throughout the software development lifecycle (SDLC)
Ensure alignment with best practices in cloud platforms (Azure, AWS, or GCP), security, and DevOps
Document architectural decisions, diagrams, and technical artifacts in both English and Spanish when necessary
Collaborate with product, engineering, and sales teams to deliver both client-facing and internal solutions
App development mobile and web applications
Requirement:
Advanced English
5-7 Years of experience:
Experience as a Solutions Architect or in a similar role
Hands-on experience in architecting SaaS applications using cloud platforms (Azure, AWS, or GCP) At least two of them.
Solid understanding of data engineering concepts such as ETL/ELT pipelines, data lakes, data warehouses, and streaming
Familiarity with microservices architecture, serverless computing, containerization (Docker/Kubernetes), and CI/CD pipelines
Experience communicating effectively with both technical and non-technical stakeholders, in English and Spanish
Solid understanding of data engineering concepts: ETL/ELT pipelines, Data lakes, Data warehouses and Streaming data
Experience with API design and integration (REST and GraphQL)
Expertise in architecting SaaS applications using cloud platforms (Azure, AWS, or GCP).
1-3 Years of experience:
Experience integrating AI/ML models into cloud applications
Hands-on experience with AI/ML frameworks and integrating models into cloud applications
Recuerda que ningún reclutador puede pedirte dinero a cambio de una entrevista o un puesto. Asimismo, evita realizar pagos o compartir información financiera con las empresas.