A Software Engineer seeking opportunities in AI and backend systems. Experienced in building LLM-based applications, including RAG solutions and evaluation frameworks, with a focus on scalability, reliability, and performance. Familiar with cloud infrastructure, ML pipelines, and distributed systems. I'm a hands-on builder, particularly interested in model behavior and system reliability.
Python, Java, C#, SQL, HTML/CSS, Bash, FastAPI, Spring MVC, React, ASP.NET MVC, REST APIs, Microservices
LangChain, LangGraph, LlamaIndex, Anthropic Claude, Retrieval-Augmented Generation (RAG), AI Agents, Multi-Agent Systems, Prompt Engineering, Function Calling, Structured Outputs, RAGAS
NVIDIA Triton Inference Server, TensorRT-LLM, LangSmith, Apache Kafka, Inference Optimization, Performance Monitoring, LLM Evaluation
PostgreSQL, MySQL, MongoDB, Redis, FAISS, SQL, NoSQL
AWS, Google Cloud Platform, Cloud Storage, Cloud Pub/Sub, Compute Engine, GPU/TPU, Azure DevOps, Docker, Kubernetes, Terraform, Git, CI/CD
Postman, VS Code, PyCharm, IntelliJ IDEA, Gradle
Most teams optimise the wrong layer. This piece unpacks why Model Context Protocol is the missing link between retrieval performance and real inference efficiency.
Read on LinkedIn ↗Training gets the headlines, but inference is where AI either scales or stalls. A breakdown of the latency, throughput, and cost trade-offs engineers rarely talk about.
Read on LinkedIn ↗Hallucination gets all the attention, but abstention is the harder engineering problem. Explores how production systems can be designed to gracefully decline uncertain queries.
Read on LinkedIn ↗Empirical findings on where LLMs fall short against domain experts in translation tasks — and what that means for how we benchmark language model capability.
Read on LinkedIn ↗An interactive visual essay inspired by Jensen Huang's framework for understanding the full AI stack — from silicon to application.
Read More ↗A breakdown of ETL vs ELT pipelines — three stages, key differences, when to use each, and related concepts like Data Warehouses and MPP databases.
Read More ↗A breakdown of cache types and placement — external, CDN, in-process, client-side — plus read/write patterns like cache-aside, write-through, and write-behind, and the cache stampede failure mode.
Read More ↗A deep dive into REST, GraphQL, and RPC — covering resource modeling, HTTP methods, RBAC auth, and rate limiting with real examples from a Ticketmaster-style system.
Read More ↗I love meeting new people. I respond to all emails.