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Shruti Gaikwad
Mid-Level Software Engineer specializing in secure cloud microservices and FinTech
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About
Built and owned major parts of a real-time distributed AI fraud-detection pipeline (ingestion, inference microservice integration, and automated action layer), optimizing latency and observability and reducing false positives by ~35%. Understands ROS/ROS2 concepts (nodes/topics/services) and planned hands-on ramp-up via ROS2 pub/sub exercises and Gazebo simulation, but has not worked on physical robots or ROS in production.
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Key Strengths
- Owned end-to-end components of a real-time AI decision pipeline (ingestion, inference integration, action/control layer)
- Reduced false positives ~35% via threshold tuning
- Improved latency and reliability through caching and bottleneck isolation
- Structured debugging approach: profiling, controlled reproduction, logging/tracing, end-to-end validation with live traffic patterns
- Strong understanding of modular, deterministic real-time system design
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