Senior Software Engineer | 11+ Years Building Scalable Backends (TDD) | Creating Self-Learning Systems with Generative AI, RAG & CAG
Senior backend engineer with 11+ years of experience architecting scalable, test-driven systems that serve millions of users. Specialized in building self-learning systems leveraging generative AI, retrieval-augmented generation (RAG), and cache-augmented generation (CAG) frameworks.
- Architecture: Distributed systems design, microservices, event-driven architecture
- Engineering Practices: TDD, CI/CD, code review leadership, mentoring
- AI/ML Integration: LLMs, RAG/CAG pipelines, embeddings, zero-shot learning
- Performance: System optimization, caching strategies, database tuning
- Python (Django, FastAPI), TypeScript/Node.js
- AWS, GCP, Kubernetes, Docker
- PostgreSQL, MongoDB, Redis
- Apache Kafka, RabbitMQ
- Generative AI pipelines & LLM integrations
- Vector databases & semantic search
- PyTorch, TensorFlow ecosystems
- RAG & CAG framework implementation
- React.js, Next.js, Server Components
- TypeScript, GraphQL
- Tailwind CSS
- Building production-ready RAG and CAG systems
- Optimizing vector databases for enterprise scale
- Implementing cost-effective AI/ML pipelines
- Integrating caching strategies for LLM response optimization
- Portfolio: nikhilbhagat.com.np
- Email: programmer@nikhilbhagat.com.np
- LinkedIn: Connect with me
- Implemented RAG and CAG systems that reduced customer support costs by 35%
- Architected backend systems handling 10M+ daily requests
- Reduced cloud infrastructure costs by 40% through architecture optimization
- Led TDD implementation that reduced production bugs by 70%