I'm a software engineer and MSCS student at Arizona State University focused on building reliable backend systems, data-intensive platforms, and practical AI tools.
Over the last two years in fintech, I've built Spring Boot services for partner onboarding, digital lending, compliance automation, and API monitoring. My work includes reducing partner onboarding from 12 days to 2 days, building APIs that sustain 100+ TPS, and developing internal platforms that improved compliance productivity by 60%.
I'm most energized by engineering problems involving latency, correctness, distributed systems, and unstructured data. I enjoy taking ideas from architecture to production-whether that means designing APIs, building microservices, creating full-stack tools, or adding AI workflows where they create real value.
Outside of work, I love building side projects, playing chess, exploring new technologies, and contributing to the developer community. I also have a published research paper and enjoy competitive programming.
I'm currently open to backend, API developer, platform, full-stack, and applied AI software engineering intern roles.(Summer 2026 internships)
Distributed analytics platform with geohash-based sharding across MongoDB clusters and LLM-powered natural language query interface, achieving P95 latency <600ms across 2M+ NYC traffic records.
3-phase deterministic analytics engine scoring career transitions using real-time O*NET, BLS, and JSearch APIs. Features Oxford-formula automation risk scoring, skill overlap analysis, and a guardrail validation engine for explainable, reproducible feasibility reports.
Built a multi-agent RAG pipeline with Planner, Researcher, Critic, Analyst, and Reporter agents. Aggregates data from 20+ real-time sources with Bayesian probability calibration to generate market forecasts in under 9 minutes.
Built voice-first mock interview platform with 3D Three.js office scene, real-time speech transcription via Speechmatics, Claude-powered STAR framework scoring with sentence-level analysis, adaptive follow-ups, and spoken feedback with word-by-word highlighting.
End-to-end platform converting hand-drawn wireframes to HTML/CSS using CNN+CTC model and OpenCV, with React live editor and Flask backend - reducing prototyping time by 30%.
Evaluated and benchmarked LSTM, BERT, CodeBERT, and CodeGPT models for Java code completion on 10K+ GitHub repos, analyzing Top-K accuracy and scalability trade-offs.
Course Work: Fall '25: Distributed Database Systems, Statistical Machine Learning, Knowledge Representation & Reasoning
Spring '26: Semantic Web Mining, Perception In Robotics, Software Verification, Validation & Testing
Strong foundation in CS fundamentals, data structures, algorithms, and software engineering. Published research in Springer Nature.
I'm currently open to backend, API developer, platform, full-stack, and applied AI software engineering internship opportunities.
If you're hiring or think there's a strong fit, feel free to reach out through LinkedIn or email.
