Autonomous Car UI
Real-time 3D vehicle interface rendering live ROS2 sensor data — LiDAR, camera, velocity — in the browser using Three.js. One of very few browser-based autonomous vehicle HMIs.
// founding engineer · jagriq · available
GenAI · Full Stack · Autonomous Systems
Founding Engineer at Jagriq, building GenAI products from first principles. Previously at RoshAI — shipped a 3D real-time autonomous vehicle interface and a production robotics fleet management system.
I work across the full stack: LLM pipelines and FastAPI backends to interfaces consuming live ROS2 sensor streams.
I started building at the intersection of AI and systems before it had a name. My undergraduate focus in AI & ML at HITS Chennai gave me the fundamentals — but the real education came from shipping production systems: a robotics fleet manager that orchestrates real AMRs, and a browser-based 3D interface rendering live sensor data from an autonomous vehicle.
Today I'm a Founding Engineer at Jagriq, where I own the product architecture end-to-end — from LLM pipeline design to the frontend that makes it usable. I've deployed to AWS, Azure, and GCP, written backends in FastAPI, Django, and Spring Boot, and built mobile apps in Flutter alongside server-driven UIs in Next.js.
What I'm actually interested in: systems that are observable, architectures that don't require heroics to maintain, and AI interfaces that feel like tools — not toys.
Education & Certifications
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Real-time 3D vehicle interface rendering live ROS2 sensor data — LiDAR, camera, velocity — in the browser using Three.js. One of very few browser-based autonomous vehicle HMIs.
Full-scale robotics fleet management system built on OpenRMF. Real-time robot status, task queuing, multi-floor map visualisation, and CI/CD-automated Docker deployment.
End-to-end container recognition pipeline: YOLO detects, LangChain reasons, FastAPI serves, PostgreSQL stores. Production-deployed with sub-second inference.
Automated test case generation for autonomous driving simulations. LangChain builds scenario trees stored in Neo4j — traversable knowledge graphs for edge case coverage.
Manufacturing component QA — YOLOv7 anomaly detection deployed on Azure with Docker, automated scoring, and a dashboard for inspection engineers.
AES-encrypted password vault: Flutter mobile app + Next.js web + Node.js API + MySQL. Single codebase serving iOS, Android, and browser.
// constantly expanding
Interesting problems. Ambitious products. People who care about the craft. If that sounds like your project — I'd like to hear about it.