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Ramya Jonnala

Principal/GenAI Engineer specializing in LLMs, RAG, and MLOps

Plano, TXGen AI Engineer9 years experiencePrincipalArtificial IntelligenceMachine LearningEnterprise Software
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About

Built a production AI-powered university marking system that automates question generation and grading from PDF course materials using a RAG pipeline (S3 + Pinecone) orchestrated with LangChain/LangGraph and deployed on AWS ECS via Docker/ECR and GitHub Actions CI/CD. Addressed a key real-world LLM challenge—grading consistency—by implementing rubric-based scoring, retrieval re-ranking, and standardized context summarization, validated against human instructors.

Experience

Gen AI EngineerAmplifAI
Principal Software EngineerVeripark software private limited
Software EngineerPositive Edge Technology private limited
Jr. Data ScientistIndium Software

Education

Texas A&M University – San Antoniomaster, Computer Science (2025)

Key Strengths

  • Built and deployed production LLM system end-to-end (RAG + containerization + AWS ECS)
  • Designs reliable multi-step agent workflows with validation and fallback logic
  • Improves LLM output consistency via rubric-based scoring decomposition
  • Strong retrieval quality focus (chunking, re-ranking, context normalization) for factual grounding
  • Pragmatic model/prompt selection using experimentation, A/B tests, and cost-awareness
  • Testing discipline for LLM systems (unit + end-to-end + edge cases) with human-in-the-loop evaluation
  • Effective collaboration with non-technical stakeholders (professors) and iterating prompts from feedback

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Languages

English

Skills

PythonJavaScriptTypeScriptC#SQLScikit-learnPandasNumPyTensorFlowPyTorchKerasMatplotlibSeabornJupyter NotebookDjango