• Build and deploy RAG-based chat systems for enterprise knowledge management and internal tooling • Design multi-agent orchestration workflows using LangChain, LangGraph, and custom frameworks • Develop and optimize voice AI agents for customer interactions and automated communications • Implement computer vision solutions for authentication, monitoring, and automated processing • Architect scalable backend services using Python, FastAPI, and Pydantic for data validation • Design and maintain RESTful APIs that integrate AI capabilities with existing business systems • Build event-driven workflows and automation pipelines using tools like n8n and Pub/Sub systems • Implement webhook integrations with third-party services (CRMs, communication platforms, databases) • Deploy AI services across GCP (Vertex AI, Cloud Run, Cloud Functions) and AWS (Lambda, Rekognition, DynamoDB) • Containerize applications using Docker for consistent deployment environments • Optimize cloud resource usage and implement cost-effective AI solutions • Manage data pipelines between cloud storage, databases, and ML models • Build SQL-based data extraction and transformation workflows using BigQuery and PostgreSQL • Create automated reporting and visualization systems using PowerBI or similar tools • Implement machine learning models for classification, prediction, and anomaly detection • Perform data analysis to inform AI system improvements and feature development