S Dheeraj Reddy
Open to work1 years experienceSoftware Engineer
Software Engineer specializing in AI/ML, LLMs, and scalable backend systems.
Standing Rank
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Developer Badges
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Skills & Technologies
35 skillsWork Experience
Software Engineer - AIML
Siemens
- Designed and implemented scalable backend services and REST APIs using FastAPI and PostgreSQL, improving response latency and system throughput across modules.
- Built and deployed a distributed RAG-based knowledge system leveraging Vector Databases and LLMs across 100+ repositories, optimizing large-scale semantic retrieval and improving debugging efficiency across engineering workflows.
- Engineered GraphQL APIs integrating GraphRAG and Knowledge Graphs to enable intelligent retrieval across Siemens Energy data, reducing data over-fetching by 45% and improving API response time by 35%.
- Developed LLM-powered semantic search using GraphRAG, RAG, PEFT, and Knowledge Graphs, reducing developer query resolution time by 30%.
- Containerized and deployed AI services using Docker, AWS, and CI/CD pipelines, reducing deployment time by 40% while improving scalability and reliability.
Software Engineering Intern
Automation Anywhere
- Developed reusable automation solutions using JavaScript, TypeScript, Python, REST APIs, and backend validation modules, improving framework maintainability, reducing manual testing effort by 25%, and increasing execution efficiency by 30%.
- Built scalable automation utilities for production systems, identified 40+ critical defects, contributed to two production releases with a 98% success rate, and collaborated with engineering teams to debug and optimize software quality..
Projects
Emotion-Based Song Recommendation System
- Constructed a full-stack emotion-driven recommendation workflow (Angular + FastAPI + SQLite) delivering real-time music suggestions with 100ms response latency.
- Engineered feature-extraction and inference pipelines using Keras, Mediapipe, and OpenCV, improving extraction efficiency by 20%.
Network Bug Triage & Remediation Platform
- Implemented an LLM-assisted triage pipeline achieving 95% fault localization accuracy across RDMA and kernel failures, enabling faster root-cause analysis and significantly improving incident response efficiency.
- Developed a hybrid retrieval + classifier workflow (NLP + XGBoost) and automated remediation with Ansible (canary + rollback), improving prioritization accuracy by 40% and reducing resolution time by 35% and manual debugging effort by 60%.
Leaderboard Standings
Leaderboard Position Pending
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Assessment Highlights
Assessments Not Completed
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AI Collaboration Score
AI Collaboration Score Pending
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Role Compatibility Profile
Role Compatibility Analysis Pending
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Achievements
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About Details
Professional Bio
Software Engineer with experience building AI applications, scalable backend systems, and LLM-powered solutions using Python, FastAPI, React, TypeScript, and cloud-native technologies. Hands-on experience in AI Agents, Prompt Engineering, GraphRAG, Knowledge Graphs, and Vector Databases.
Minor in Data Science and Artificial Intelligence
Indian Institute of Technology Ropar, India (2024 - 2025)
Bachelor of Engineering in Information Science and Engineering
BMS Institute of Technology and Management, Bangalore, India (2021 - 2025)