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Lakshmi Vivek Jagabathina
Mid-Level Software Developer specializing in Java/Spring microservices and Salesforce
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About
Backend/AI engineer who built an AI icon-generation SaaS backend (Java/Spring Boot, MongoDB) on AWS, including async job processing with idempotency and S3-based result storage to handle traffic spikes. Also shipped applied AI in finance—an end-to-end fraud detection pipeline with risk scoring—and designed a banking support AI agent with strict guardrails, audit logs, and human-in-the-loop escalation.
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Key Strengths
- Built and operated production backend APIs on AWS with monitoring (CloudWatch)
- Diagnosed and resolved latency/timeouts under traffic spikes via async job processing, caching, and DB indexing
- Designed reliable async workflows with idempotency and rate-limit handling (exponential backoff/retries)
- End-to-end ownership of an ML fraud detection pipeline from data prep through deployment and monitoring
- Designed AI agent workflows with separation of planning vs execution, tool error handling, and human escalation
- Strong production engineering practices in Python: modular architecture, typing, testing, and observability
- Relational schema design and query performance optimization using composite indexes and query restructuring
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