Full Stack Engineer with 1+ years in AI/ML & Cloud Technologies
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Assessing your cultural and operational fit
Full-Stack Engineer with 1.9 years of experience, AWS Certified in Machine Learning. Proficient in developing and enhancing investigation platforms, multi-tenant ATS systems, and LMS platforms. Skilled in Spring Boot, ReactJS, FastAPI, MongoDB, and deploying AI/ML models using AWS, LLMs, and various ML algorithms. Adept at automating workflows and managing secure, scalable applications on cloud infrastructure.
Malnad College of Engineering, Hassan
Bachelor of Engineering · Information Science and Engineering
N/A – June 30, 2025
Texas AI
Associate Software Engineer
March 1, 2025 – Present
Bengaluru, Karnataka, India
Mipzo EdTech Pvt Ltd
Innovation Technical Intern
October 1, 2024 – February 1, 2025
Hassan, Karnataka, India
NeuroSpectra: AI Healthcare Diagnostic Tool
June 1, 2026 – Present
Developed full-stack AI application using FastAPI backend for Autism Spectrum Disorder prediction with 99.98% accuracy. Implemented Support Vector Machine (SVM) classifier, benchmarked against Random Forest and Logistic Regression models. Built form validation and progressive data collection UI with real-time feedback for medical professionals.
View ProjectLeo – Ride Booking Platform – Consulting Project
June 1, 2026 – Present
Architected and developed a full-stack ride booking platform consisting of Driver, Rider, and Admin applications using React Native, Spring Boot, and MongoDB. Designed and implemented RESTful microservices for ride booking, driver allocation, trip lifecycle management, and user authentication. Integrated Google Maps APIs for geolocation and route tracking, Twilio for real-time ride notifications, and Razorpay for secure payment processing. Deployed backend services on AWS, building scalable APIs and implementing cloud-based infrastructure to support ride operations and admin monitoring.
AgroIntent: AI Crop Assistant
June 1, 2026 – Present
Built an AI-powered crop diagnostic tool using Vertex AI (Gemini 2.5 Flash) that converts farmer text/photo inputs into structured diagnosis cards with urgency level and confidence scoring. Deployed serverless FastAPI backend on Google Cloud Run with rate limiting, input validation, and Cloud Logging; frontend on Firebase Hosting. Implemented voice I/O and multi-language support (English, Hindi, Kannada, Telugu, Tamil) via Web Speech API with zero added latency.
View ProjectAWS Certified Machine Learning Engineer – Associate
AWS
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, including professional consulting projects, academic AI applications, and contributions to an ATS platform, demonstrates a broad interest in technology and a willingness to tackle different problem domains. The involvement in a technical club and organizing events suggests a collaborative spirit and leadership potential. The blend of backend, frontend, and AI/ML skills aligns well with a dynamic, innovation-focused environment. The candidate's experience with multiple programming languages and frameworks indicates adaptability, which is a positive cultural fit for evolving tech teams.
Soft Skills & Operational Fit
The candidate's project descriptions and work experience indicate a proactive approach to problem-solving and a capacity for independent work. Leadership experience in a technical club suggests organizational skills and the ability to foster collaboration. The focus on optimizing data retrieval and automating workflows points to an efficiency-driven mindset. However, without direct interview data, specific soft skills like direct communication style, conflict resolution, or adaptability in a team setting cannot be fully assessed.