name: Shubhang S
role: Backend & DevOps Engineer
focus:
- Production ML / LLM infrastructure (RAG, multi-agent systems)
- Cloud-native infrastructure, GitOps & DevOps automation
- Distributed systems & backend scalability
- Observability & self-healing infra
developing:
- advanced ML
- DevOps
- backend
- cloudI build production-grade ML & backend systems — from RAG and multi-agent LLM infrastructure down to the cloud-native platforms and GitOps pipelines that keep them running reliably.
- Designing production ML systems — retrieval pipelines, rerankers, and reliability/safety layers for agentic LLM workloads
- Shipping Kubernetes, GitOps, and IaC workflows with full observability (Prometheus + Grafana)
- Strong focus on performance, reliability, and self-healing infrastructure
- Hands-on with scalable backend architectures and automated, verifiable infra pipelines
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A transactional safety layer for multi-agent LLM systems.
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Schedules container workloads across compute providers to minimize cost.
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Answers questions grounded in your own documents, built to run in prod.
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Simulates, verifies, and certifies infra fixes before they hit prod.
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Real-time network threat hunting combining vision + retrieval.
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6-class transformer-based NLP classifier.
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| Area | What I'm Exploring |
|---|---|
| Production ML / LLM Infra | RAG systems, rerankers, multi-agent LLM reliability & safety |
| Advanced ML | Transformers, ViT, retrieval & evaluation pipelines |
| DevOps & GitOps | Autonomous remediation, Kubernetes automation at scale |
| Cloud-Native Backend | Async APIs, distributed systems, AWS + Terraform IaC |
| Observability | Metrics, tracing & self-healing infrastructure |
"Build systems that heal themselves."



