Design, develop, and implement AI agents using modern frameworks such as LangChain, LlamaIndex, Semantic Kernel, and Databricks Agents
Integrate AI agents with diverse enterprise data sources including APIs, Databricks Lakehouse, internal platforms, and unstructured document repositories
Build end-to-end AI/ML pipelines using Databricks Lakehouse, MLflow, Workflows, and Unity Catalog
Enable and optimize Retrieval-Augmented Generation (RAG) workflows for enterprise AI applications
Collaborate with engineering, data science, and platform teams to deliver enterprise-grade AI automation and insights
Work closely with product and business stakeholders to validate use cases, refine hypotheses, and align AI solutions with business outcomes
Implement best practices in data architecture, agent evaluation, automation strategies, and secure data access
Monitor and evaluate AI agents using frameworks such as DeepEval, RAGAS, TruLens, PromptFoo, LangSmith, and OpenTelemetry for LLMs
Ensure secure integration using OAuth2, OIDC, JWT, RBAC, and regulated data access patterns
Support deployment of cloud-native services including microservices, APIs, containers, and Kubernetes environments
