AI Engineer specializing in Agentic AI, Generative AI, LLM Systems, and Data Engineering
AI Engineer with 4+ years of experience building production-grade AI and data systems. I specialize in Python, LLMs, agentic workflows, RAG, real-time data pipelines, and distributed data platforms. My work spans AI assistants, self-service analytics, streaming systems, risk analytics, and data-intensive backend infrastructure. I focus on turning AI capabilities into reliable, observable, and production-ready systems rather than isolated prototypes.
Building production-grade agentic AI systems, AI intelligence layers, and data-driven decision systems with LLMs, tool-using agents, real-time pipelines, and scalable backend infrastructure.
Implementation of FlashAttention-style tiled multi-head attention kernels in C++/CUDA and custom PyTorch C++ extensions with benchmark comparisons.
A zero-copy, fault-tolerant distributed streaming engine built in Rust for processing 1.5M+ events/sec with sub-millisecond p99 stateful window aggregations.
An automated regression and evaluation suite for testing complex RAG retrieval, multi-hop reasoning, tool invocations, and semantic drift with synthetic dataset generation.
Spearheading real-time streaming infrastructure, distributed data marts on Azure Databricks, graph-based recommendation engines, and self-serve AI analytics platforms.
Designed high-throughput Python ELT pipelines, AI assistant backends for healthcare triage, and automated lab scoring engines.
Developed configuration-driven ETL workflows, cloud storage lifecycle archival pipelines, and cost-optimized data marts.
A deep dive into Key-Value caching mechanics, memory fragmentation bottlenecks, PagedAttention, Multi-Query Attention (MQA), and speculative prefix caching.
How memory-mapped buffers, cache line alignment, and Apache Arrow columnar formats eliminate serialization overhead in high-throughput analytical streaming.
Why vibe-checking fails in production: designing synthetic datasets, calibrated LLM-as-a-judge rubrics, trajectory state checking, and statistical significance testing.