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Backend and DevOps ☸️
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Backend and DevOps ☸️

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Pushkarmondal/README.md
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Founding Engineer · Backend & Cloud Systems · AI/GenAI

Typing SVG


Twitter LinkedIn Portfolio LeetCode

Profile Views


┌─────────────────────────────────────────────────────────────────────────┐
│  $ cat impact.log                                                        │
└─────────────────────────────────────────────────────────────────────────┘
🚀 Metric 📊 Result 🛠 Method
Users Served Production backend shipped
Time to Revenue Post-launch execution
Infra Cost ARM migration
OOM Crashes Heap profiling
CI/CD Self-healing pipelines

┌─────────────────────────────────────────────────────────────────────────┐
│  $ ls -la /specializations                                               │
└─────────────────────────────────────────────────────────────────────────┘
drwxr-xr-x  backend_systems/        → APIs, async queues, job processors
drwxr-xr-x  cloud_infrastructure/   → AWS, Docker, K8s, Terraform
drwxr-xr-x  ai_genai_engineering/   → RAG pipelines, LLMs, embeddings
drwxr-xr-x  devops_sre/             → CI/CD, heap profiling, cost ops
-rw-r--r--  philosophy.txt          → minimal, fault-tolerant, no drama

┌─────────────────────────────────────────────────────────────────────────┐
│  $ tech --list --filter=production-grade                                 │
└─────────────────────────────────────────────────────────────────────────┘

Languages & Runtimes

TypeScript Node.js Python

Backend & APIs

Express Fastify FastAPI

Data & Storage

PostgreSQL Prisma Redis MongoDB Elasticsearch

AI / GenAI Systems

LangChain Pinecone OpenAI Qdrant HuggingFace

Infrastructure & Cloud

AWS Docker Kubernetes Terraform Nginx

Observability

Grafana Kibana Kafka


┌─────────────────────────────────────────────────────────────────────────┐
│  $ tail -f /var/log/learning.log                                         │
└─────────────────────────────────────────────────────────────────────────┘
[INFO]  Hybrid search — BM25 + dense retrieval + cross-encoder reranking
[INFO]  Agentic patterns — ReAct, Plan-and-Execute, LangGraph
[INFO]  RAG evaluation — RAGAS, RAPTOR, Self-RAG architectures
[INFO]  MLOps infra — LangFuse, experiment tracking, production evals
[INFO]  pgvector — embedding storage at scale inside Postgres
[DEBUG] Reading: RAGAS, RAPTOR, ReAct, Self-RAG (12-week paper sprint)

📐 System Design notessystemdesign.nishitdevs.xyz


┌─────────────────────────────────────────────────────────────────────────┐
│  $ cat ~/.engineering_principles                                          │
└─────────────────────────────────────────────────────────────────────────┘
class EngineeringPhilosophy:
    execution   = "Ship it. Harden it. No over-engineering."
    reliability = "Systems that stay up when traffic spikes."
    cost        = "Every dollar of infra spend is a deliberate choice."
    code        = "Flat structure. Direct calls. No unnecessary abstractions."
    ai_usage    = "Minimal, pragmatic, always questioned."

┌─────────────────────────────────────────────────────────────────────────┐
│  $ git log --stat --summary                                              │
└─────────────────────────────────────────────────────────────────────────┘

GitHub Streak


┌─────────────────────────────────────────────────────────────────────────┐
│  $ ping pushkar --open-to=US-remote-roles                                │
└─────────────────────────────────────────────────────────────────────────┘

Open to: Early-stage startups · AI/GenAI roles · US remote · Backend / Infra / MLOps

Twitter LinkedIn Portfolio


> Systems that survive. Code that ships. No drama.

Built with intention, not a template generator. ⚡

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