• Project Mission: To serve as the chief technical authority for the project, designing a robust and scalable architecture that bridges the gap between the business vision and technical implementation. This role ensures the platform is built on sound engineering principles and aligns with long-term enterprise strategy.
• Key Responsibilities: o Design the end-to-end technical architecture for a generative AI-powered data analytics platform. o Define the core data flow, including how user queries are processed, how context is retrieved (e.g., Retrieval-Augmented Generation), and how AI models are invoked. o Make critical technology stack decisions, such as selecting the appropriate vector database, orchestration frameworks, and model integration patterns. o Lead architectural reviews and deep-dive sessions with development teams to ensure a shared understanding of the technical design. o Oversee the integration of all system components, including frontend applications, backend services, AI models, and underlying data sources. o Ensure the architectural design correctly enforces enterprise security and compliance requirements, particularly regarding data access and authorization. o Mentor development leads and provide technical governance throughout the project lifecycle.
• Required Skills & Experience: o Extensive experience as a Solutions Architect, with a focus on data platforms and cloud-native applications. o Deep, hands-on expertise in Generative AI concepts, including RAG patterns, prompt engineering, embeddings, and frameworks (e.g., LangChain, LangGraph). o Strong understanding of modern data architecture paradigms, such as Data Mesh, data warehousing, and data lakes. o Expertise in containerization (Docker) and orchestration platforms (Kubernetes, OpenShift, GKE). o Proven ability to communicate complex technical concepts to both technical and non-technical stakeholders.
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