AI Engineer · Data Engineer · Full Stack Developer
Building production-grade intelligent systems — agentic AI, big data pipelines, edge inference, and reinforcement learning. 7 deployed systems across 8+ national and international hackathons.
I am an AI Engineer focused on building production-grade intelligent systems. Bridging the gap between pure research and practical application, I design architectures that don't just train well, but deploy seamlessly. My work spans agentic workflows, deep reinforcement learning, and data analytics, backed by full-stack engineering expertise.
I believe true AI engineering happens beyond the model weights. It requires rigorous data engineering, robust backend infrastructure, and scalable system design. I don't just train models — I architect end-to-end autonomous systems that solve complex, real-world problems.
Subscription Revenue Intelligence Pipeline
Big data ETL/ELT pipeline ingesting 200K+ billing events across 500 SaaS tenants with MRR/ARR/churn analytics.
Event-Driven Medallion Analytics Platform
Bronze→Silver→Gold medallion data lake design mirroring enterprise-grade sustainable technology data lake architecture.
High-Throughput Ingestion Pipeline
High-throughput secure ingestion pipeline optimized from nested vectorization bottlenecks to 417 rec/s via pre-caching.
Confidence-Gated Support Intelligence
Uncertainty-aware AI routing engine that detects ambiguous B2B SaaS tickets before misrouting.
Autonomous Production Incident Resolution
Autonomous RL agent for resolving production infrastructure incidents 3.1× faster than human L1.
Semiconductor Edge AI
Stream-aware edge inference pipeline for real-time 300mm wafer defect inspection.
XGBoost + SHAP Explainability
End-to-end predictive pipeline on 18,000+ climate and soil records for agricultural forecasting.
Meta PyTorch OpenEnv 2026 Finalist (Easy 0.906 · Medium 0.887 · Hard 0.650). Competed in Microsoft Imagine Cup and UIDAI Data Hackathon, producing 5 production-style pipelines under intense deadlines.
Led 6+ hackathon teams as Technical Lead. Mentored a national hackathon team to selection by architecting the solution, preparing technical documentation, and training teammates through end-to-end design.
Built and deployed 7+ real-world intelligent systems, including Reinforcement Learning environments, stream-aware edge AI engines, and enterprise medallion data lakehouses handling 200K+ workloads.
"Experience is presented as a high-density technical ledger. We avoid narrative-heavy descriptions in favor of Monospace metadata blocks and bulleted impact metrics, echoing the aesthetics of a system log."