UTA MSIS • SOFTWARE ENGINEER • ML + CLOUD
Current Software Engineer at DoJoGa, former engineer at TCS, and a University of Texas at Arlington Master's graduate in Information Systems. I blend backend engineering, MLOps, and cloud DevOps into production-ready systems.
I’m the kind of engineer who loves hard problems: distributed systems, high-availability Linux workloads, cloud architecture, and ML systems that move from notebook experiments to reliable pipelines. I’ve worked on backend/cloud systems at DoJoGa, engineered CI/CD and software workflows at Tata Consultancy Services, and constantly build side projects across AI, analytics, and modern DevOps.
I actively participate in tech communities and events including AI-focused symposiums and hands-on innovation forums. My goal is to build impact-heavy, intelligent platforms that are both developer-friendly and business-ready.
Recent participation includes events and symposiums hosted by The University of Texas at Arlington, Microsoft AI Tour, and Dallas AI community meetups.
Designing and shipping backend-first software systems that are cloud-native, reliable, and production-ready. I build Python/Java services, optimize APIs, containerize workloads with Docker, and deploy to Kubernetes/AWS. My focus is software engineering excellence: scalable architecture, clean code, testability, observability, and AI-assisted development practices for faster and safer release cycles.
Contributed across the SDLC in enterprise engineering teams: requirement understanding, design, implementation, testing, CI/CD automation, release support, and production reliability. Built and maintained developer workflows with GitHub Actions, worked in distributed Linux environments, and collaborated on cloud migration and system modernization.
A curated set of projects from my GitHub portfolio (ML, MLOps, backend, and cloud engineering).
FastAPI + Kubernetes + observability stack with production-style deployment and security hardening.
Open Repository ↗CI/CD workflows, infrastructure automation, and GenAI experiments documenting practical engineering learnings.
Open Repository ↗Accident risk prediction pipeline with real-world data and API integration for predictive mobility insights.
Open Repository ↗NLP and ML pipeline to classify fraudulent job posts with robust data preprocessing and model evaluation.
Open Repository ↗Weather-informed predictive analytics for traffic severity using feature engineering and ML optimization.
Open Repository ↗Explore more builds on my full GitHub profile ↗.
End-to-end software engineering capabilities across frontend, backend, cloud, SDLC, and AI-driven delivery.
Career XP: 0 ⚡
Responsive UI architecture, component-based design, accessibility-first UX, performance-focused rendering, and modern JavaScript workflows.
API design, microservices, distributed systems, Java/Spring Boot services, Python backends, database integration, caching, and secure service communication.
AWS, Docker, Kubernetes, Terraform, CI/CD pipelines, GitHub Actions, observability, and high-availability Linux operations.
Requirement analysis, architecture, coding standards, code reviews, test-driven development (TDD), release management, and continuous improvement.
Data science workflows, feature engineering, machine learning modeling, MLOps fundamentals, AI analytics, and AI-driven development accelerators.
The University of Texas at Arlington (UTA)
Electronics and Instrumentation Engineering
Represented student voices, contributed to campus initiatives, and supported student-success programs.
Recognized multiple times in 2022 at TCS for high-impact delivery, ownership, and engineering excellence.
Earned the HackerRank Software Engineer role certification (issued Jan 18, 2026), demonstrating strong coding fundamentals.
Attended UTA symposiums, Microsoft AI Tour, and Dallas AI events to stay ahead in AI/ML innovation.
Real snapshots from awards, leadership, graduation, and AI/analytics events.
Certificates and event snapshots are integrated to validate achievements, leadership, and active community participation.
Predicted Accident Risk Score: 0.00
Easter Egg: try the Konami code ↑ ↑ ↓ ↓ ← → ← → b a
Let’s build something unforgettable in ML, backend engineering, or cloud DevOps.