Design and develop AI agents using modern frameworks such as LangChain, LlamaIndex, Semantic Kernel, and Databricks Agents
Architect scalable multi-agent systems enabling collaboration, shared context, autonomous execution, and human-in-the-loop workflows
Build secure and optimized integrations between AI agents and enterprise data sources including APIs, Databricks Lakehouse, internal platforms, and unstructured datasets
Leverage Databricks (Lakehouse, MLflow, Workflows, Unity Catalog) to build end-to-end AI/ML pipelines and enable RAG workflows
Lead and mentor engineers, specialists, and data scientists in AI/ML tools, agent frameworks, and best practices
Partner with global cross-functional stakeholders to deliver AI-driven automation and actionable insights
Collaborate closely with business and product sponsors to align AI initiatives with strategic opportunities through hypothesis validation and predictive modeling
Define strategic approaches for innovative data usage and influence enterprise data design decisions
Establish best practices for agent evaluation, monitoring, feedback loops, and performance optimization
Ensure secure data access governance using OAuth2, OIDC, JWT, RBAC, and compliant access patterns for regulated datasets
