Azure AI/ML Cloud Architect for Data Platforms

Cloud Hybrid Technologies, LLC; San Jose (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Cloud Hybrid Technologies, LLC in San Jose seeks a Cloud Architect with strong AI/ML (Azure) to design, build, and evolve our cloud-based data architecture. 5+ years of data engineering and Azure experience are required, with hands-on delivery of end-to-end pipelines and governance.

You will oversee strategy, select services, ensure security, and collaborate with data scientists and engineers. The role requires EST hours and a focus on scalable, real-time and batch workloads, MLOps, and

Qualifications

• Bachelor's degree in CS, Data Science, or related field.
• 5+ years hands-on data engineering with distributed computing (Spark/MapReduce/Databricks).
• Proven Azure cloud-based data solution design experience.
• Strong data modeling and DB skills (relational + NoSQL).
• Excellent diagramming skills (Visio, Lucidchart).

Responsibilities

• Strategize roadmap development for end-to-end cloud analytics and AI adoption.
• Design AI/ML workflows: ingestion, training, deployment, monitoring.
• Select cloud services and platforms to fit requirements.
• Design scalable distributed cloud solutions for real-time and batch workloads.
• Implement MLOps, CI/CD for ML models.
• Ensure security, privacy, and governance compliance.
• Collaborate with stakeholders, engineers, and data scientists.
• Monitor performance and optimize resources.
• Create architecture diagrams and documentation.
• Drive innovation via pilots and PoCs.

Skills

AI/ML Architecture

Data Engineering

Azure Cloud

Kubernetes

Data Modeling

SQL/NoSQL

Diagramming

Education

Bachelor's degree in Computer Science or related field

Tools

Databricks

Azure Data Lake

Spark

Hadoop

Visio/Lucidchart

Job description

Cloud Hybrid Technologies, LLC in San Jose seeks a Cloud Architect with strong AI/ML (Azure) to design, build, and evolve our cloud-based data architecture. 5+ years of data engineering and Azure experience are required, with hands-on delivery of end-to-end pipelines and governance.

You will oversee strategy, select services, ensure security, and collaborate with data scientists and engineers. The role requires EST hours and a focus on scalable, real-time and batch workloads, MLOps, and