Open to opportunities

Dheemanth Raviraj

@dheemanthraviraj

Software engineer focused on AI-enabled backend systems, real-time telemetry, and automation for reliable production impact.

United States

Message

What I'm looking for

I’m looking for a role where I can build AI-enabled backend systems and agentic automation, ship reliable production services, and work closely with engineers to turn real-world requirements into measurable impact.

I’m a software engineer building production-ready systems that blend backend engineering with AI-driven automation and agentic workflows. Currently, I’m pursuing a Master of Science in Software Engineering at Arizona State University.

In my capstone role, I engineered a real-time telemetry platform using Raspberry Pi, BLE, and FastAPI to monitor controlled assets across Scottsdale Fire Department vehicles, turning telemetry into dashboard notifications and audit logs to improve accountability.

As an intern at Star Knowledge, I deployed FastAPI microservices into a production healthcare backend, replacing rule-based classification with NLP-driven inference for a 25% accuracy gain and a 40% user engagement lift. I also helped reduce Azure production incidents by 35% through structured monitoring and logging, and I’ve continued exploring agent reliability and RAG performance through projects like VerifyFlow, ResearchForge, and a Developer Intelligence Agent.

Experience

Work history, roles, and key accomplishments

Software Engineer (Capstone)

Scottsdale Fire Department

Jan 2026 - May 2026 (4 months)

Engineered a real-time telemetry platform using Raspberry Pi and BLE with FastAPI to monitor drug boxes and narcotics pouches across department vehicles and detect misplaced assets. Built backend processing and alerting workflows to generate dashboard notifications and audit logs for improved accountability of controlled substances.

Raspberry Pi fastAPI Telemetry Backend Alerting Audit Logging

Software Engineer Intern

Star Knowledge

Nov 2022 - Nov 2023 (1 year)

Deployed five FastAPI microservices into a production healthcare backend, removing manual scheduling bottlenecks and enabling real-time workflow automation. Improved classification by replacing rule-based logic with NLP-driven inference (25% accuracy gain, 40% engagement lift) and supported monitoring/logging improvements to reduce production incidents by 35%.

fastAPI Python Microservices Workflow Automation NLP Azure Monitoring Logging

Education

Degrees, certifications, and relevant coursework

Arizona State University

Master of Science, Software Engineering

2024 - 2026

Grade: 4.00/4.00

M.S. in Software Engineering at Arizona State University (Tempe, AZ) from 2024 to 2026 with a GPA of 4.00/4.00. Coursework included Data Processing at Scale and Software Verification/Validation/Testing.

JSS Science and Technology University

Bachelor of Engineering, Computer Science and Engineering

2019 - 2023

Grade: 9.44/10.0

B.E. in Computer Science and Engineering at JSS Science and Technology University (Mysore, Karnataka, India) from 2019 to 2023 with a GPA of 9.44/10.0.