Agent Architecture & Workflow Design
Consult with internal and client teams to determine which agent workflows need to be created for specific use cases.
Define capabilities, intents, and interaction flows of AI agents to meet business goals.
Design the system architecture for multi-agent orchestration and model integration.
Model Strategy & Execution
Guide the selection, fine-tuning, and integration of LLMs, RAG pipelines, and transformer-based models.
Define how models will interact with different data modalities (text, audio, video, structured data).
Evaluate and benchmark model performance and retraining needs.
Data Enrichment & Intelligence
Advise on how to configure, enrich, and pre-process data (structured/unstructured) for maximum model performance.
Oversee entity extraction, topic modeling, summarization, and other NLP-driven enrichment techniques.
Ensure data pipelines are designed for continuous learning and improvement.
Solution Implementation & Code Ownership
Lead prototyping and MVP development, translating architecture into production-grade solutions.
Collaborate with developers to build scalable AI services and interfaces.
Write clean, efficient, and modular code to integrate AI components.
