Lakshmi Durga Karanam

• Design and develop Generative AI–powered applications using large language models (LLMs) to enable intelligent data interaction and automated insights. • Build and optimize retrieval-augmented generation (RAG) workflows to improve accuracy, contextual relevance, and reliability of AI responses. • Develop backend services and AI integrations using Python to support scalable, production-grade AI features and automation capabilities. • Improve AI system performance by optimizing prompt strategies, model interactions, and response workflows for better efficiency and accuracy. • Collaborate with cross-functional teams including data engineering, product, and platform teams to design and deploy AI-driven solutions. • Contribute to the development and deployment of production AI systems that enhance internal analytics, decision support, and operational efficiency.

Developed ML models for fraud detection, risk analytics, and customer segmentation using Python, TensorFlow, PyTorch, XGBoost Assisted in building RAG-powered AI assistants and LLM-driven chatbots to support financial insights and customer service Worked with AWS SageMaker and Azure AI for training and fine-tuning ML/LLM models Contributed to ETL pipelines using Spark, Hadoop, and SQL for data preparation and processing Supported integration of vector databases (Weaviate, Pinecone) for semantic search and document intelligence Helped create dashboards with React/Angular for visualization and reporting

Developed Python-based REST APIs and automation pipelines to streamline workflows, reducing manual processing and improving operational efficiency. Migrated legacy applications to Flask and FastAPI microservices, enhancing scalability, maintainability, and deployment reliability. Designed ETL processes with Python and Pandas, enabling near real-time data availability and improving reporting workflows. Built and optimized SQL and NoSQL database integrations (MySQL, MongoDB), improving query performance and system stability. Implemented CI/CD pipelines with Jenkins and GitLab, cutting deployment time by 50% and minimizing production issues. Collaborated with clients and cross-functional teams to deliver solutions aligned with business goals and requirements.

Focused on the intersection of technology and business strategy, with coursework in Software Engineering, Data Analytics, Database Systems, IT Strategy, and Project Management. Developing skills in Python, SQL, system design, and data-driven decision-making, while gaining hands-on experience in solving real-world IT challenges.

Studied a combination of electronics and computer science subjects, with emphasis on Data Structures, Algorithms, DBMS, Operating Systems, and Object-Oriented Programming. Gained practical experience through labs and projects using C, C++, Java, and Python, along with a strong foundation in digital systems and communication technologies.