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Neel Patel
Mid-level Python Backend Engineer specializing in cloud-native and AI-powered systems
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Backend/AI engineer who has shipped an LLM-powered enterprise support-ticket agent at Comcast, building a production-grade microservices pipeline (FastAPI, SQS, Redis) with strong observability (OpenTelemetry/Splunk/Prometheus/Grafana) and reliability patterns (async, caching, circuit breakers, idempotency). Demonstrated quantified impact at scale—processing 10k+ tickets/day while improving response SLAs and routing accuracy through evaluation and human feedback loops.
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Key Strengths
- Shipped LLM ticket-processing agent to production at Comcast (summarization, sentiment, routing)
- Production reliability engineering for LLM systems (async handling, caching, circuit breakers, fallbacks)
- Designed multi-step agent orchestration with microservices + SQS + Redis state management
- Built observability and monitoring stack (OpenTelemetry, Splunk, Prometheus, Grafana) with measurable uptime targets
- Scaled workflow to 10,000+ tickets/day with zero message loss and 99.99% uptime (as stated)
- Delivered measurable business impact: 15 hours/week manual effort reduced, 20% faster first response time, 30% higher recommendation/routing accuracy
- Implemented eval + feedback loops and error analysis to improve routing accuracy (30%) and reduce error rates (20%)
- Improved high-severity ticket detection via preprocessing + reweighted routing logic (+18% detection accuracy, -25% misclassification)
- Handled messy ERP-like data with schema validation (Pydantic), idempotency, and quarantine workflows; reduced data-related API errors by 40% and prevented duplicate transactions
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