Rushmitha Parvathaneni

About Rushmitha Parvathaneni

AI Engineer with over 5 years of experience in designing and deploying scalable data pipelines, optimizing cloud-based data ecosystems, and implementing AI-driven solutions using Python, NLP, and Large Language Models (LLMs) with frameworks like LangGraph and LangChain. • Expert in automating complex ETL workflows using AWS services (Glue, Lambda, Redshift, S3) and Azure platforms, achieving up to 70% reduction in manual processing time while ensuring data integrity and reliability for enterprise-grade analytics. • Proficient in evaluating and fine-tuning LLMs for tasks such as text classification, ticket routing, and response generation, leveraging RAG architectures and vector search to enhance model accuracy by 25% and reduce hallucination rates to under 3%. • Certified AWS Data Engineer with hands-on expertise in building robust data lakes, orchestrating data workflows, and integrating cloud-native tools like Snowflake, Azure Databricks, and AWS SageMaker for high-performance analytics and model deployment. • Skilled in developing real-time dashboards using Tableau, QuickSight, and React, enabling stakeholders to derive actionable insights from complex datasets, improving operational efficiency by up to 30%. • Experienced in MLOps practices, utilizing CI/CD pipelines, Docker, and Kubernetes to deploy production-ready AI models, ensuring seamless integration with business applications and scalable performance. • Strong collaborator in Agile environments, leading cross-functional teams to align technical solutions with business objectives, driving data-driven decision-making and measurable outcomes like cost reductions and enhanced customer engagement. • Passionate about leveraging advanced analytics, statistical modeling, and Generative AI to solve complex business challenges, delivering innovative solutions across logistics, healthcare, and telecommunications domains.

Experience

1. Generative Ai Engineer

   Sunovee

   May 2025 — Present · Clayton, NC, US

   Built an end-to-end RAG-based conversational AI system on Google Cloud Platform (GCP) to support customer assistance, maintenance, troubleshooting, and intelligent vendor appointment scheduling workflows. Designed and implemented a scalable document ingestion pipeline on GCP to process using DocLing and LlamaParser, including document parsing, metadata extraction, validation, normalization, and storage. Implemented document chunking and indexing using LlamaIndex, generated semantic embeddings with OpenAI text-embedding-3-small, and stored vectors in Qdrant to enable fast, accurate, and low-latency similarity search across large document sets. Integrated Large Language Models (LLMs) to generate context-aware, grounded responses, combining retrieved document context with structured prompts to improve answer accuracy and reduce hallucinations. Orchestrated multi-step, intent-driven workflows using Google Agent Development Kit (ADK), dynamically routing customer queries across retrieval, reasoning, and action-based agents. Analyzed agent routing behaviour and conversation flows, evaluating whether customer questions were correctly redirected to the appropriate agent and identifying misrouting between agents. Performed sentiment analysis on customer responses, tracking resolution effectiveness, response accuracy, and user satisfaction to improve prompts, retrieval logic, and agent coordination iteratively. Deployed the system using Docker for local environments, and implemented monitoring, alerting, and tracing using Prometheus, Grafana, Phoenix, and Evidently AI, along with synthetic health checks to proactively detect agent failures and performance. Implemented MLOps operations, including data drift and target drift detection and continuous evaluation to ensure reliability in production. Collaborated with cross-functional stakeholders to translate business requirements into scalable AI solutions and present insights to non-technical audiences.

Education

• Manipal Institute of Technology

  Bachelor of Technology, Electrical and Electronics Engineering

  2017 — 2021

• Northeastern University

  Master of Science - MS, Data Analytics Engineering