About the Role
Seeking a technically engaged Enterprise Architect skilled in data platforms, AI/ML workflows, and cloud infrastructure across AWS, Azure, and GCP to lead the end-to-end architecture of an AI Training Data Service platform, from blueprint design to implementation guidance and cloud service selection.
Responsibilities
- Define the overall architecture for an AI training data platform
- Design scalable and secure system components
- Lead technical decision-making for cloud infrastructure
- Select appropriate cloud-native services across providers
- Develop architecture blueprints and design documentation
- Ensure alignment with enterprise AI readiness goals
- Integrate third-party tools and platforms
- Collaborate with engineering teams on implementation
- Guide development teams in technical execution
- Evaluate and recommend technology stacks
- Maintain consistency across system layers
- Optimize for performance and reliability
- Support deployment strategies
- Address technical debt and scalability challenges
- Ensure compliance with security standards
- Work with data governance frameworks
- Balance innovation with operational stability
- Translate business needs into technical designs
- Drive architectural consistency across services
- Support incident resolution through design improvements
- Document architectural decisions
- Stay current with cloud and AI trends
- Provide technical leadership
- Foster collaboration between teams
- Ensure platform interoperability
Nice to Have
- Experience with AI model lifecycle platforms
- Familiarity with data labeling systems
- Knowledge of MLOps practices
- Prior work in AI training data services
- Experience integrating commercial AI tools
- Background in data quality frameworks
- Exposure to hybrid cloud environments
- Involvement in platform modernization initiatives
Work Arrangement
Remote (Country)
Role Overview
We are looking for a hands-on Enterprise Architect with strong technical expertise in data platforms, AI/ML lifecycle, and multi-cloud architecture (AWS, Azure, GCP). This role will define and implement the end-to-end architecture and design for Cognizant’s AI Training Data Service (AITDS) platform, ensuring it is scalable, secure, and optimized for enterprise AI readiness. This position requires deep technical involvement—from designing architecture blueprints to selecting cloud-native services, partnering with external products and guiding implementation.
