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Platform Architect
Job summary
A leading technology firm is seeking an AI Platform Architect to design and guide the technical infrastructure supporting AI initiatives. The role involves collaboration with teams to ensure seamless deployment of AI solutions, focusing on scalable and secure systems. Candidates should have a Bachelor's or Master's degree and at least 8 years of experience in AI/ML architecture, with deep expertise in cloud platforms like AWS, Azure, and GCP. This position offers an opportunity to work on cutting-edge AI technologies in a dynamic environment.
Qualifications
- Minimum 8 years of experience in AI/ML architecture and infrastructure design.
- Deep expertise in cloud platforms (AWS, Azure, GCP) and on-premise systems.
- Strong understanding of MLOps, data engineering, and integration frameworks.
Responsibilities
- Design and advise on the AI/ML system architecture for cloud and on-premise infrastructure.
- Support the selection and onboarding of AI platform vendors and ecosystems.
- Ensure platform scalability, performance, and security across AI use cases.
- Collaborate with data engineering and MLOps teams for seamless deployment.
Skills
Education
The AI Platform Architect is responsible for designing and guiding the technical infrastructure that supports AI initiatives across the organization. This role ensures the selection and integration of scalable secure and high-performance AI/ML platforms whether cloud-based or on-premise while avoiding vendor lock-in and maintaining access to cutting-edge capabilities.
The architect supports the evaluation and onboarding of vendor ecosystems advises on infrastructure decisions and ensures seamless integration with data engineering and MLOps pipelines. This role is critical to enabling Omantels AI solutions to be robust future-proof and aligned with enterprise architecture standards.
Design and advise on the AI/ML system architecture including cloud and on-premise infrastructure.
Support the selection onboarding and engagement of AI platform vendors and ecosystems.
Ensure platform scalability performance and security across AI use cases.
Advise on infrastructure evaluation and integration strategies.
Collaborate with data engineering and MLOps teams to ensure seamless deployment and operations.
Prevent vendor lock-in while enabling access to advanced AI capabilities.
Support solution capability development and infrastructure optimization.
Bachelors or Masters degree in Computer Science Engineering or related field.
Minimum 8 years of experience in AI/ML architecture and infrastructure design.
Deep expertise in cloud platforms (AWS Azure GCP) and on-premise systems.
Strong understanding of MLOps data engineering and integration frameworks.
Proven experience in vendor evaluation onboarding and ecosystem management.
Knowledge of infrastructure scalability performance tuning and security best practices.
Excellent problem-solving communication and stakeholder engagement skills.
Staff IC
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.