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Software Development Engineer with 1+ years in Backend, AI & Data Analytics
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Experienced Software Development Engineer with 1.2 years of combined expertise in backend development, AI, and data analytics. Proficient in Python, JavaScript, TypeScript, and C++, with a strong command of frameworks like FastAPI, Node.js, and Express.js. Skilled in leveraging AI technologies such as LangChain and RAG pipelines to build robust solutions, enhance system performance, and drive data-driven insights across diverse projects.
University School of Information, Communication & Technology (GGSIPU)
MCA · Software Engineering
September 1, 2023 – July 1, 2025
Aryabhatta College (University of Delhi)
B. Sc. (H) · Computer Science
October 1, 2019 – July 1, 2022
CARNOT RESEARCH PRIVATE LIMITED
Software Development Engineer
February 1, 2025 – January 1, 2026
India
TWILEARN
Data Analyst Intern
January 1, 2023 – February 1, 2023
India
ORQESTRA
June 27, 2026 – Present
Built an autonomous API integration platform using a 5-agent LangGraph workflow (Planner, Researcher, Code Generator, Evaluator, Repo Context) that analyzes APIs and generates production-ready integration code. Designed a fault-tolerant LLM orchestration layer across 3 model providers (Gemini, Groq, OpenRouter) with automatic failover, Redis-backed cooldowns, and 30-second execution guards. Engineered a self-healing monitoring framework that detects API contract drift, runtime failures, and integration regressions, triggering automated repair workflows with up to 3 recovery attempts. Developed a RAG-powered validation pipeline using FastMCP, Jina embeddings, and LLM-based evaluation loops to improve integration accuracy and reduce redundant model calls.
PINGDAEMON
June 27, 2026 – Present
Architected a backend-driven website monitoring system capable of handling 70+ monitored services with scheduled health checks. Designed RESTful APIs for uptime and latency analytics, achieving 90%+ monitoring reliability under concurrent workloads. Deployed Celery-based async workers on a VPS using Docker for scalable production use.
Cultural Fit Analysis
The candidate's involvement in open-source projects (GSSOC'24) and competitive programming indicates a collaborative and growth-oriented mindset. The diversity of projects, from AI integration platforms to website monitoring and chatbots, shows adaptability and a broad interest in different technical challenges. Their academic background and continuous learning (MCA) align with a culture of continuous improvement. The experience with an on-premise incident management system suggests an ability to work within structured and secure environments.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving abilities through competitive programming and open-source contributions. Their project descriptions indicate a proactive approach to system design, fault tolerance, and performance optimization. The experience with managing Linux-based services suggests operational awareness. The detailed project descriptions also highlight good communication of technical achievements.