The Company:
Cognizant (NASDAQ:CTSH) is a leading provider of information technology, consulting, and business process outsourcing services, dedicated to helping the world's leading companies build stronger businesses. Headquartered in Teaneck, New Jersey (U.S.), Cognizant has over 340,000 employees as of January 2025. Cognizant is a member of the NASDAQ-100, the S&P 500, the Forbes Global 1000, and the Fortune 500 and is ranked among the top performing and fastest growing companies in the world.
Job Summary:
The AI Architect is a visionary technical leader responsible for designing and implementing the organization's AI infrastructure. This role demands deep expertise in AI systems architecture, cloud computing, data engineering, and security. The AI Architect will ensure that AI solutions are scalable, secure, and seamlessly integrated with existing platforms, enabling the organization to leverage AI for strategic advantage.
Key Responsibilities:
- Design and develop robust, scalable, and secure AI infrastructure architectures.
- Evaluate and select appropriate AI platforms, tools, and technologies.
- Ensure seamless integration of AI solutions with existing enterprise systems and data sources.
- Develop and maintain architectural standards, best practices, and guidelines for AI development.
- Lead the design and implementation of data pipelines and data storage solutions for AI applications.
- Collaborate with AI Engineers, Data Scientists, and MLOps Engineers to ensure alignment of architectural designs with project requirements.
- Conduct performance analysis and optimization of AI systems.
- Stay abreast of emerging AI technologies and trends and provide recommendations for their adoption.
- Address security concerns and build privacy focused systems.
Qualifications:
- Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related field.
- Minimum of 8 years of experience in AI systems architecture and design.
- Deep expertise in cloud computing platforms (e.g., AWS, Azure, GCP) and AI services.
- Strong understanding of data engineering principles and practices.
- Proven experience in designing and implementing scalable and secure AI solutions.
- Excellent communication and collaboration skills.