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Sragvi Vadali
Junior Software Engineer specializing in AI/ML and real-time systems
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About
Backend/AI engineer who built a real-time vector database system for high-frequency financial data using Kafka/Flink on Kubernetes, achieving sub-100ms similarity search at 10k+ concurrent load and resolving tricky duplication issues with idempotency/versioning. Also shipped an end-to-end LLM-based travel itinerary feature (profiling + prompt workflows + APIs) with a focus on quality consistency and low latency.
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Key Strengths
- Built real-time vector-search backend with Kafka/Flink and Kubernetes
- Scaled system to 10,000+ concurrent inputs with sub-100ms query latency
- Debugged and fixed large-scale data duplication via idempotency, deterministic event IDs, versioning, and checkpoint alignment
- Shipped LLM-powered travel itinerary feature end-to-end (profiling, prompts, backend, deployment) with <3s latency target
- Strong production Python practices: DI, typing (pyright), async timeouts, dependency pinning, unit tests
- Improved PostgreSQL query performance (cut query times in half)
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