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Vaibhav Dabhi
Mid-Level Full-Stack Software Engineer specializing in Java microservices and cloud-native delivery
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About
Built and shipped a production LLM feature that explains DSA problems with real-life explanations, using Grok with automatic failover to OpenRouter (and multiple backup models) to avoid user-facing failures. Improved cost efficiency by implementing difficulty-based token budgets and iterated prompt quality via structured constraints and an in-app feedback mechanism, reporting satisfaction across 38 users.
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Key Strengths
- Designed resilient LLM inference with circuit-breaker failover across multiple providers/models
- Reduced LLM token usage/cost by introducing difficulty-based token budgets (easy/medium/hard)
- Iterated prompts using explicit rules/constraints and user feedback to improve output quality
- Built an in-app feedback loop and used it to drive ongoing refinements
- Delivered a production feature with reported satisfaction from 38 active users
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