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Pranav Purathepparambil
Intern Software Engineer specializing in distributed systems and security
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About
Built a production LLM-powered analyst assistant at Discern Security to speed up SOC investigations using a RAG pipeline over security vendor documentation (Python PDF ingestion, vector search). Demonstrates deep, security-critical LLM engineering: structure-aware chunking with custom table parsing, grounded/cited responses, prompt-injection defenses, and post-generation validation, validated via golden datasets and adversarial testing; tool is used daily by analysts.
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Key Strengths
- Built and deployed a production RAG system for SOC investigations
- Improved retrieval quality via structure-aware chunking and custom PDF table parsing
- Designed security-critical LLM guardrails (grounded prompting, citations, prompt-injection defenses, post-gen validation)
- Strong evaluation discipline (golden datasets, adversarial cases, component unit tests, end-to-end tests, retrieval metrics, latency checks)
- Pragmatic model/retrieval selection based on stakes, latency, and grounded behavior
- Effective collaboration with non-technical SOC stakeholders through iterative live demos and workflow alignment
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