Backend & AI Engineer building scalable distributed systems, event-driven pipelines, and production-grade LLM infrastructure.
I specialize in designing and operating distributed backend systems that handle real-world production workloads reliably and efficiently.
Currently working as an AI Engineer at Insurance Samadhan, where I:
- Architect Kafka-based event-driven microservices
- Build production LLM + RAG pipelines
- Optimize backend systems for throughput and latency
- Design fault-tolerant async processing workflows
- Implement observability and centralized logging infrastructure
Key Impact:
- Increased system throughput 3×
- Reduced backend latency by 56%
- Lowered infrastructure costs by 92%
- Improved document extraction accuracy by 40%
Distributed Systems
- Kafka, Redis, Event-Driven Architecture
- Idempotent Consumers, Dead-Letter Queues
- Async Processing & Concurrency Control
- Horizontal Scaling & Caching Strategies
AI Systems Engineering
- Production LLM Applications
- RAG Pipelines & Embeddings
- Vector Databases
- AI Workflow Optimization
Backend Engineering
- Python, Node.js, TypeScript
- FastAPI, Django, Express.js
- REST, gRPC, WebSockets
- MongoDB, PostgreSQL
Observability & Infrastructure
- Prometheus, Grafana
- Centralized Logging Systems
- Docker, AWS, GCP
A cryptographically verifiable, time-sortable distributed identifier system designed for high-concurrency environments.
- 18-byte compact format
- HMAC-SHA256 signature validation
- Monotonic sequencing with deterministic conflict resolution
- Benchmarked with 10M+ parallel ID generations (zero collisions)
Repository: https://github.com/KishanKumar08/veridjs
- Design for failure from day one
- Optimize for performance and cost
- Build systems that scale predictably
- Keep architecture clean and observable
- Ship AI systems that work in production, not demos
LinkedIn: https://www.linkedin.com/in/kishan-kumar08/
Email: kmali4551@gmail.com