Tejaswi karre

Spearheaded enterprise agentic AI workflows with secure API integration and RAG evaluation. Led engineering plans for agent orchestration, tool permissions, test coverage, and controlled production rollout. Engineered and validated enterprise RAG pipelines across Azure AI Search, OpenSearch, and Pinecone, achieving ~92% retrieval precision through RAGAS/TruLens and Azure AI Foundry evaluations. Implemented secure agent-to-system integrations using OAuth 2/OIDC, JWT validation, RBAC, and least-privilege tool execution to enforce authorization boundaries between LLM decisions and sensitive banking operations. Built reusable Python/Pytest validation frameworks covering LLM decisions, REST API contracts, authentication failures, and end-to-end workflows, enabling repeatable quality gates before releases. Strengthened production reliability via CI/CD quality gates, distributed tracing, and observability with OpenTelemetry, Prometheus, and Grafana, supporting 99.95% service availability.

Engineered Kafka-based enterprise integrations processing 2M+ records daily, reducing batch execution time by 40%. Modernized AWS-hosted workloads and application data integrations, reducing manual reconciliation by 35%. Implemented automated validation and testing controls, reducing production defects by 30%. Improved CI/CD pipelines using Jenkins and AWS CodePipeline to support daily deployments with 99.9% pipeline uptime. Strengthened application security with JWT, RBAC, and audit logging while supporting production incident resolution. Supported Docker and Kubernetes deployments, improving release consistency by 50% via automated testing and code reviews.

Modernized enterprise healthcare services using Spring Data, Hibernate, Oracle, and MongoDB, improving data retrieval performance by 25%. Optimized database queries and application integrations, improving clinical reporting performance by 25%. Led resolution of 100+ application defects, strengthening release reliability through Agile delivery and CI/CD improvements. Developed Azure Data Factory integrations processing 1M+ healthcare records daily, reducing data latency by 40%.