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Yashwanth J
Mid-level Software Engineer specializing in LLM agentic AI and full-stack systems
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About
Full-stack engineer at Bank of America who built and iterated a real-time transaction monitoring/fraud detection system processing 50K+ daily transactions, improving latency (25%), dashboard performance (30%), and reducing manual investigation time (40%) while meeting PCI DSS via OAuth2 and RBAC. Also built a scalable ETL pipeline for messy financial data with strong reliability/observability (ELK, retries, DLQ), boosting data integrity from 87% to 99% and sustaining 99.8% uptime.
Experience
Education
Key Strengths
- Owned end-to-end real-time fraud/transaction monitoring feature (design → build → launch → iterate)
- Scaled system processing 50,000+ daily transactions with security and performance focus
- Reduced system latency by 25% via optimized SQL and Hibernate caching
- Implemented OAuth 2.0 + RBAC to meet PCI DSS compliance requirements
- Post-launch iteration driven by user feedback: richer alerts and filtering to prioritize cases
- Reduced false positives by refining detection algorithms and adding validation rules
- Improved dashboard load times by 30%
- Reduced manual investigation time by 40% through workflow/product improvements
- Built scalable ETL pipeline for messy multi-source financial data with schema validation and edge-case handling
- Improved data integrity from 87% to 99% and maintained 99.8% uptime with observability (ELK) and reliability patterns (retries, DLQ)
- Designed latency/cost tradeoffs using batching for non-critical data and real-time processing for high-priority transactions
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