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Sugathri Gotu
Mid-Level Full-Stack Software Engineer specializing in FinTech and cloud-native microservices
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About
Built and shipped a production LLM-powered incident response agent for a microservices platform, automating alert triage and safe remediation recommendations with strong guardrails (RAG grounding, structured JSON outputs, rule-based validation, and human-in-the-loop). Implemented state-machine orchestration (Redis/Kafka), comprehensive eval/monitoring, and an error categorization pipeline that cut hallucination errors ~40% and reduced MTTR ~30%.
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Key Strengths
- Shipped production LLM incident-response agent with ~99.9% uptime and rule-based fallbacks
- Reduced incident MTTR by ~30% via automated alert analysis and guided remediation
- Designed robust LLM guardrails (structured outputs, confidence thresholds, whitelisted actions, human approval for risky steps)
- Architected multi-step agent orchestration with state machines (Redis/Kafka), retries/timeouts, and rollback/escalation paths
- Built offline/online evaluation and monitoring loops; reduced hallucination-related errors by ~40% through RAG + stricter schemas + thresholds
- Created an error categorization pipeline (rule-based + LLM labeling) with dashboards to drive targeted reliability improvements
- Handled messy operational/ERP-like data with normalization, schema validation, strict permissions, idempotency, and dry-run checks
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