Enterprise Architect

• Define enterprise architecture for AI/GenAI-powered applications and platforms .
• Design solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings, vector databases, prompt engineering, and AI agents .
• Architect hybrid search solutions combining vector search, keyword search, metadata filtering, and semantic retrieval .
• Design AI workflows that integrate enterprise data, business rules, APIs, and decision engines.
• Establish patterns for AI governance, security, explainability, observability, evaluation, and responsible AI.
• Evaluate emerging AI technologies and determine their applicability to enterprise use cases.
• Design scalable LLM integration patterns supporting multiple models and model providers.
• Lead architecture and development of highly scalable Java/J2EE and Spring Boot applications.
• Define standards and reference architectures for microservices, REST APIs, event-driven architecture, and distributed systems .
• Design highly available and fault-tolerant services capable of supporting high-volume transaction environments.
• Provide technical leadership in areas including concurrency, performance optimization, caching, resiliency, and distributed transactions.

Establish reusable Java frameworks, libraries, design patterns, and engineering standards.