// Applied AI Engineer
I build practical AI products across model behavior, backend systems, and infrastructure — prompt engineering, agent workflows, and production reliability that improve quality, reduce cost, and solve real user problems.
01/About
I build applied AI systems that are useful in production, reliable under pressure, and grounded in real product outcomes.
At Vizly, I work across prompt design, agent behavior, backend systems, and cloud infrastructure to improve how AI products perform in the real world. My recent work includes building secure MCP integrations with OAuth, shipping enterprise prompt-governance features, and reducing infrastructure costs without sacrificing reliability.
I enjoy working at the layer where model quality, product experience, and engineering rigor meet. Whether I’m debugging production issues, designing data workflows, or building AI-powered developer tools, I care about making systems practical, measurable, and easy for people to trust.
Southfield, MI (Remote)
Snapshot
Applied AI Engineer at Vizly.ai, Inc.
June 2025 – Present
Arizona State University
Aug 2023 – May 2025 · Tempe, AZ
Amrita Vishwa Vidyapeetham
Jul 2017 – Jun 2021 · Coimbatore, India
02/Skills
A comprehensive toolkit for building intelligent data-driven solutions
03/Projects
Real-world projects spanning AI, data science, and software engineering — solving complex business and technical challenges
Feb 2026 – Present
Architecting a multi-tenant SaaS health platform with provider-agnostic AI routing, enterprise RBAC, Postgres RLS, and Langfuse observability. Engineering Fitbit OAuth 2.0 PKCE integration with encrypted token storage and resumable 90-day Inngest backfill workflows, alongside cache-first food search and privacy-focused data export/deletion flows.
Aug 2023 – Dec 2023
Trained a unified deep learning pipeline across CheXpert, ChestX-ray14, MIMIC, VinDr-CXR, and ChestX-Det to classify, localize, and segment chest X-rays using a student-teacher contrastive learning architecture with cyclic pretraining to mitigate catastrophic forgetting. Applied ConvNeXt for classification, Faster R-CNN-ResNet for localization, and UNet-Swin for segmentation, achieving AUC 0.7348 on ChestX-ray14, mAP 0.115 on VinDr-CXR, and Dice 0.4711 on ChestX-Det using 2x A100 CUDA GPUs. Developed as part of a joint medical imaging research initiative between Arizona State University and Mayo Clinic, contributing deep learning solutions to assist radiologists in early and accurate detection of pulmonary conditions.
04/Experience
Building intelligent systems and leading data-driven initiatives across various industries
Vizly.ai, Inc.
June 2025 – Present
Southfield, MI (Hybrid)
Aggregate Intelligence Inc.
May 2024 – Aug 2024
Remote
Aggregate Intelligence Inc.
Sep 2022 – May 2023
Coimbatore, India
Algolitics India LLP
May 2019 – Jun 2019
Coimbatore, India
05/Contact
Interested in applied AI, intelligent product work, or building something useful together? Reach out and let's start the conversation.
Share a bit about what you're building, hiring for, or exploring and I'll take it from there.
Usually responds within 24 hours