Building AI systems. Leading engineering teams. Turning ideas into production.
Senior backend engineer and technical lead working across AI engineering, distributed systems, cloud architecture, and scalable backend platforms.
I care about software that is not only intelligent, but also reliable, secure, observable, maintainable, and production-ready.
- Multi-model LLM application architecture
- Retrieval-augmented generation and grounded responses
- Embeddings, chunking, retrieval, reranking, and citations
- Agentic workflows, tool integration, orchestration, and MCP
- Model-provider abstraction across OpenAI, Anthropic, Gemini, Azure OpenAI, and compatible APIs
- Evaluation, observability, prompt-injection defense, and production reliability
- Vector databases and semantic search
- Hybrid retrieval and metadata filtering
- Query rewriting, reranking, and relevance tuning
- Knowledge-base architecture and document-processing pipelines
- Search, caching, indexing, and data-access design
- REST and async APIs
- Distributed systems and service boundaries
- Event-driven architecture and background workers
- Queues, caching, idempotency, and concurrency
- Authentication, RBAC, multi-tenancy, and secure API design
- Testing, performance, maintainability, and observability
- Building complete product flows around backend and AI services
- Streaming conversational interfaces and real-time UX
- API integration, state management, and production-facing workflows
- Keeping frontend architecture simple while backend systems carry the complexity
- Azure Blob Storage, Service Bus, Event Grid, Key Vault, and managed services
- AWS Lambda, S3, RDS, ECS, and queue-driven workloads
- Dockerized development and deployment
- CI/CD, secure configuration, secrets, and environment management
- Monitoring, failure recovery, and production operational patterns