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Pravalika Kasojjala
Mid-level AI/ML Engineer specializing in LLM, RAG/GraphRAG, and fraud analytics
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About
LLM/agent engineer who has deployed a production internal assistant to reduce employee inquiry resolution time while maintaining regulatory compliance. Experienced with RAG, hallucination risk triage, and graph-based orchestration (LangGraph) for enterprise/banking-style workflows, emphasizing schema-validated, citation-backed, tool-constrained agent designs and tight collaboration with non-technical business/compliance stakeholders.
Experience
Education
Key Strengths
- Built and deployed an LLM-powered internal assistant for ops/frontline policy and historical-data Q&A
- Designed RAG architectures with production focus on hallucination monitoring and feedback loops
- Risk-triaged evaluation of hallucinations based on financial/compliance impact
- Strong agent/workflow reliability practices: tool constraints, node-level contracts, schema validation, fallbacks, mandatory citations
- Pragmatic model and retrieval selection: constraints-first, escalate model size only when needed, tune chunking/overlap
- Bridges business/compliance requirements into explainable AI workflows with clear success metrics and fast stakeholder feedback
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