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Sai Bandaru
Mid-level Machine Learning Engineer specializing in fraud detection and LLM systems
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About
At FiVerity, built and deployed a production LLM/RAG-based Information Gathering Tool for credit union fraud analysts that generates auditable investigation summaries from verified evidence. Focused on high-stakes constraints—hallucination prevention, cross-entity leakage controls, compliance/PII-safe monitoring, and latency—while also shipping customer-facing agentic workflows using CrewAI and LangGraph in close partnership with fraud and compliance stakeholders.
Experience
Education
Key Strengths
- Built and deployed production RAG system for fraud investigation summaries with auditable outputs
- Strong guardrails approach: strict schemas, verified-evidence-only generation, post-generation validation
- Experience mitigating hallucinations and preventing cross-entity data leakage in multi-tenant environments
- Pragmatic evaluation/testing: mocked + live contract tests to detect prompt drift
- Operational rigor: PII-safe monitoring and tracking workflow metrics (success rate, retries, fallbacks, latency)
- Hands-on delivery of agentic workflows (CrewAI, LangGraph) with human-in-the-loop checkpoints
- Effective collaboration with fraud analysts and compliance stakeholders to design workflows and drive customer conversion
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