Chief Information Architect

Company Description Neural Nexus is the official AI and Machine Learning club of Nitte Meenakshi Institute of Technology (NMIT), focused on building a collaborative community around artificial intelligence, machine learning, and data science. The club organizes interactive workshops, hands-on projects, and seminars to connect theoretical foundations with practical applications. Members gain opportunities to explore emerging AI technologies, contribute to real-world initiatives, and stay informed about industry trends. Neural Nexus supports learners at all levels, from beginners to advanced practitioners, providing a platform for skill development and innovation. The community is driven by curiosity, collaboration, and a shared commitment to shaping the future of AI.
Role Description The Chief Information Architect is a full-time remote role responsible for designing and overseeing the club’s information and data architecture to support projects, learning resources, and member activities. This role involves defining data models, standards, and governance practices that ensure information is accurate, consistent, and accessible for AI and machine learning initiatives. The Chief Information Architect will collaborate with student leads, project teams, and mentors to structure data for workshops, research projects, and internal tools. Daily responsibilities include documenting data flows, optimizing data storage and retrieval, and advising on information management best practices for club platforms and applications. The role also includes evaluating new tools, guiding the integration of data sources, and providing technical leadership on how information architecture can enhance collaboration and knowledge sharing.
Qualifications
Candidates should possess strong skills in Data Architecture and Data Modeling to design scalable, coherent structures for club projects and resources.
Candidates should possess skills in Information Management and Master Data Management to maintain data quality, consistency, and governance across systems and initiatives.
Candidates should possess practical experience in Data Warehousing to support analytics, reporting, and long-term storage of project and learning data.
Candidates should have familiarity with databases (SQL/NoSQL), data integration tools, and cloud-based data platforms.
Candidates should demonstrate analytical thinking, attention to detail, and the ability to document complex systems clearly.
Candidates should be comfortable working independently in a remote environment and collaborating with cross-functional student teams.
A strong foundation in AI, machine learning, or data science concepts, and prior experience in technical or architectural leadership, is highly beneficial.

Work arrangement
Yes