Design and implement scalable RAG architectures and AI Agent workflows that integrate with Oracle Fusion products
Develop sophisticated Agent-based systems utilizing frameworks like AutoGen and LangGraph to solve complex enterprise problems
Architect Multi-Agent Systems that enable collaborative problem-solving through specialized agent roles, coordination protocols, and workflow orchestration
Implement advanced prompting techniques, including chain-of-thought reasoning, tool augmentation, and context management for improved AI performance
Build advanced unstructured data search solutions utilizing Vector DBs, Reranking, Knowledge Graphs, and GraphRAG techniques
Implement comprehensive Agentic Evaluation Frameworks to assess reasoning abilities, task completion accuracy, and multi-agent collaboration effectiveness
Design Advanced Benchmarking Systems that measure agent performance across dimensions, including problem-solving capabilities, knowledge retrieval accuracy, instruction following, and reasoning transparency
Develop an automated testing infrastructure to continuously evaluate agent behaviors against adversarial prompts, edge cases, and evolving enterprise requirements
Develop distributed AI systems that can handle enterprise-scale workloads with high reliability and fault tolerance
Collaborate with product managers to understand business requirements and translate them into technical specifications
Optimize large language model performance for enterprise applications through parameter-efficient fine-tuning methods
