# Amar Mahato — Engineering Toolkit

> Evidence-backed capabilities used across backend products, cloud workflows, reliability work, and applied-AI systems. The groups explain engineering purpose rather than acting as an unfiltered keyword list.

## Backend and APIs

Service boundaries, authentication, realtime delivery, and documented contracts.

- Python
- TypeScript
- Node.js
- Express.js
- FastAPI
- REST
- WebSockets
- SSE
- JWT/JWKS
- OpenAPI

## Data, state, and storage

Durable state, queues, retrieval, and consistency under concurrent work.

- PostgreSQL
- Supabase
- Redis
- MongoDB
- SQLite
- Prisma
- Qdrant
- RabbitMQ
- row-level locking
- idempotency

## Reliability and verification

Production diagnosis, observability, automated tests, and evidence-driven evaluation.

- Sentry
- request tracing
- structured logs
- pytest
- Jest/Vitest
- benchmarks
- baselines
- retry/backoff
- audit logs
- leakage checks

## Cloud and tooling

Edge and cloud runtimes, object storage, deployment, and operator tooling.

- Cloudflare Workers
- Cloudflare R2
- Durable Objects
- AWS EC2/S3
- Docker
- GitHub Actions
- Linux
- Git
- Python CLIs
- Vercel

## Applied AI systems

Retrieval, agents, speech and document pipelines, and model evaluation inside products.

- RAG
- LangGraph
- MCP
- structured outputs
- multi-provider routing
- LangSmith tracing
- STT/OCR pipelines
- RF-DETR
- ONNX Runtime
- model evaluation
- prompt-injection checks