Software Engineer | Agentic AI | LLM Systems | Distributed Platforms
Building production-ready AI products with retrieval, tool use, orchestration, and scalable backend infrastructure.
I hold an M.S. in Computer Science from Northeastern University and work at the intersection of applied AI, LLM systems, and distributed engineering.
My focus is building reliable, scalable systems that turn AI research and prototypes into production-ready products with clear engineering impact.
- Agentic AI workflows that combine tool use, retrieval, orchestration, and external APIs to solve real tasks
- LLM applications built with RAG, fine-tuning, prompt engineering, OpenAI API integrations, LangChain, and NLP
- Scalable backend and platform systems that support production-grade AI experiences on cloud-native infrastructure
- Comfortable moving across model integration, backend services, data pipelines, and infrastructure
- Strong focus on reliability, latency, maintainability, and developer velocity
- Best fit for Applied AI Engineer, LLM Engineer, AI Platform Engineer, and backend roles for AI products
- Languages: Java, TypeScript/JavaScript, Python, Go
- AI and LLM: Agentic AI, LLM Fine-tuning, RAG, Prompt Engineering, MCP, LangChain, OpenAI API, NLP
- Frameworks: Spring Boot, Node.js, React
- Data and Messaging: Kafka, Redis, RabbitMQ
- Infrastructure: Docker, Kubernetes, Terraform
- Cloud: AWS, Google Cloud, Azure
- Databases: MySQL, PostgreSQL, MongoDB, DynamoDB, Azure Cosmos DB
Open to conversations around applied AI engineering, LLM systems, agentic workflows, distributed systems, and research-driven product development.
