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Ranjitha Narasimhamurthy
Junior Software Engineer specializing in backend systems, AI, and cloud platforms
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About
New grad candidate with graduate research experience building a multi-agent RAG pipeline from scratch, including worker-coach orchestration and an evaluation framework. Most notably, they improved structural similarity from 67% to 98% by designing validation and retry logic to reduce hallucinations, showing strong practical depth in agentic AI systems.
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Key Strengths
- Built a worker-coach multi-agent architecture from scratch
- Improved structural similarity from 67% to 98% in graduate research
- Strong agent orchestration and context handoff design
- Designed evaluation frameworks to measure multi-agent system performance
- Practical understanding of hallucination detection and retry strategies
- Thoughtful use of AI tools with strong judgment around security and correctness
- Hands-on, research-driven approach to learning AI systems
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