Design, build, and maintain data pipelines and integrations leveraging PostgreSQL Server and Snowflake for downstream AI and analytics use cases.
Own the end-to-end LLM application lifecycle — from prompt engineering and retrieval workflow design through evaluation, observability, security, and performance tuning.
Design and implement a production-grade, enterprise-class multi-agent framework that is reliable, scalable, and maintainable in live settings.
Architect and deploy multi-agent, enterprise-class AI/agentic solutions on the Azure platform, aligning with Azure-native services and best practices.
Collaborate with cross-functional stakeholders to translate business requirements into robust, enterprise-class, production-ready AI system designs.
Ensure multi-agent LLM systems meet performance, security, and observability standards before and after deployment.
Communicate technical decisions and trade-offs clearly to both technical and non-technical partners.

📌 Ai Engineer Trusaic Bengaluru
🏢 Tavant
📍 Bengaluru