What are the responsibilities and job description for the AI/ML Cloud Architect position at Azra AI?
Overview :
Join Azra AI on its mission to improve healthcare through innovative applications of natural language processing (NLP). At Azra AI, we enable health systems to enhance clinical workflows by analyzing pathology and radiology reports in real-time, identifying the presence and type of cancer, and automating registry abstraction through text extraction. These reports are presented to clinicians in an intuitive workflow tool, allowing them to provide timely care to patients while focusing on what they do best—saving lives.
Your Adventure at Azra AI :
The AI / ML Cloud Architect will lead the design, development, and implementation of cloud infrastructure to support AI and machine learning workflows. This role focuses on creating a scalable, secure, and efficient cloud environment on GCP, enabling the deployment of AI solutions in healthcare. You will be responsible for the overall architecture, cost optimization, and alignment with business goals.
Key Responsibilities :
Architect and design scalable cloud infrastructure on GCP to support AI and ML operations.
Lead the implementation of cloud solutions, ensuring scalability, security, and cost-efficiency.
Work closely with data scientists, engineers, and MLOps teams to integrate AI models into the cloud environment.
Optimize cloud infrastructure for AI workloads (e.g., GPU / TPU management, data storage, networking).
Ensure compliance with healthcare regulations (HIPAA, GDPR) and data security requirements.
Provide leadership and guidance on cloud best practices, cost management, and architecture design.
Evaluate and implement new cloud technologies that enhance the AI / ML infrastructure.
Collaborate with other teams to ensure smooth integration and deployment of AI models into production.
Qualifications :
Bachelor’s or Master’s degree in Computer Science, Cloud Engineering, or related fields.
7 years of experience in cloud architecture with a focus on AI and ML solutions.
Extensive experience with GCP (Google Cloud Platform) and its AI / ML services (Vertex AI, Kubernetes, BigQuery).
Strong knowledge of cloud security, networking, and performance optimization.
Experience in designing and implementing scalable AI / ML infrastructure in a cloud environment.
Familiarity with healthcare industry standards and data compliance requirements.
Excellent communication skills and ability to work with cross-functional teams.
