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CharanKumar Pathakamuri

Entry-Level GenAI/LLM Engineer specializing in agentic systems and RAG

Baltimore, MDGraduate Assistant (AI Research)1 years experienceEntry-LevelTechnologyArtificial IntelligenceMachine Learning
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About

LLM/AI agent engineer with consulting/contract experience (Kanhaiya Consulting LLC) who deployed a production AI agent to automate BIM list workflows end-to-end—from database understanding and data cleaning to automated visualizations/dashboards. Worked around restricted real-time data access by generating synthetic data and improving outputs via supervised fine-tuning, and uses AWS-based LLMOps observability (Opic/OPEC) plus hybrid retrieval (vector+BM25 with reranking) to optimize relevance, latency, and cost.

Experience

Graduate Assistant (AI Research)University of Maryland, Baltimore County (UMBC)
LLM EngineerKanehl Consulting

Education

University of Maryland, Baltimore County (UMBC)master, Data Science (2025)
Panimalar Engineering Collegebachelor, Computer Science (2023)

Key Strengths

  • Built and deployed an AI agent automating end-to-end data workflow (DB querying → cleaning/curation → dashboards) for BIM lists
  • Designed agent orchestration workflows using LangChain/LangGraph to enforce correct task sequencing and dependencies
  • Handled limited/partial data access by synthesizing data to validate behavior and reduce confusion around data freshness
  • Applied supervised fine-tuning to improve response quality/human-likeness
  • Uses LLMOps observability (Opic/OPEC) to optimize prompts for cost and context length post-deployment
  • Pragmatic model selection balancing complexity, latency, and budget (e.g., smaller models for high-volume simple tasks)
  • Implemented hybrid retrieval with reranking to improve relevance despite added latency

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Languages

English

Skills

Adversarial TestingAgent FrameworksAgentic AIAgentic WorkflowsAlgorithmsAWSAWS LambdaAWS S3AWS SageMakerBenchmarkingChromaDBCI/CDContext ManagementCustom RetrievalData Analysis Automation