Solution Architect

Job Description: Solution Architect Federated Data Mesh Platform for AI/ML Products

We are seeking a highly skilled and experienced Solution Architect to join our team and lead the design and implementation of a federated data mesh platform that will enable the development and deployment of cuttingedge AI/ML products. As a Solution Architect you will play a critical role in shaping the technical architecture and ensuring the scalability reliability and security of the platform.

Responsibilities:

Architect and design the federated data mesh platform: Collaborate with crossfunctional teams including data engineers data scientists and product managers to define the technical architecture and design of the platform that supports federated data governance data discovery and data sharing for AI/ML products.

Develop scalable and reliable data infrastructure: Design and implement robust scalable and highperformance data infrastructure components including data pipelines data storage and data processing systems to support the development and deployment of AI/ML models.

Ensure data security and privacy: Incorporate best practices and industry standards for data security and privacy into the platform architecture including encryption access controls and data anonymization techniques to ensure compliance with regulatory requirements and protect sensitive data.

Collaborate with crossfunctional teams: Work closely with data scientists data engineers and product managers to understand the requirements of AI/ML products and translate them into scalable and efficient technical solutions within the federated data mesh platform.

Drive platform integration and interoperability: Define and implement integration strategies and standards to enable seamless interoperability with existing systems and external platforms ensuring smooth data exchange and compatibility between different AI/ML products and services.

Evaluate and select appropriate technologies: Research and evaluate emerging technologies and tools in the AI/ML and data engineering space making informed recommendations on the adoption of new technologies that enhance the capabilities and performance of the federated data mesh platform.

Provide technical leadership and guidance: Lead and mentor a team of data engineers and collaborate with other architects and stakeholders to provide technical leadership and guidance throughout the development lifecycle ensuring adherence to architectural principles and best practices.

Stay updated with industry trends: Keep abreast of the latest trends and advancements in the field of AI/ML federated data governance and data engineering and apply that knowledge to drive innovation and improvement within the platform.

Requirements:

Software Architecture certification i.e TOGAF Azure Architect etc

Proven experience as a Solution Architect: Minimum 5 years of experience in solution architecture with a focus on designing and implementing cloudbased data platforms for AI/ML products.

Strong expertise in data engineering: Extensive knowledge of data engineering concepts including data modeling data integration data storage and data processing with handson experience in implementing largescale data infrastructure.

Familiarity with federated data governance: Experience with federated data governance models and frameworks and the ability to design and implement data governance strategies that enable efficient and secure data sharing across multiple AI/ML products.

AI/ML domain knowledge: Solid understanding of AI/ML concepts algorithms and techniques and familiarity with the challenges and requirements of deploying AI/ML models in production environments.

Proficiency in cloud technologies: Experience with cloud platforms (e.g. AWS Azure GCP) and related services for data storage compute and analytics with the ability to design and implement solutions leveraging cloudnative technologies.

Excelant experience understanding and using architecture patters i.e. Ntier Event Based Micro Services etc

Excellent experience with Agile/SCRUM methodology and using agile engineering best practices.

Strong problemsolving and analytical skills: Ability to analyze complex technical challenges identify potential solutions and make informed decisions that balance technical feasibility scalability performance and business requirements.

Excellent communication and collaboration skills: Strong verbal and written communication skills with the ability to effectively communicate technical concepts to both technical and nontechnical stakeholders and collaborate with crossfunctional teams.

Continuous learning mindset: Eagerness to stay updated with the latest advancements in AI/ML data engineering and cloud technologies and continuously expand your knowledge and skills.