Headline

Site Reliability Engineer | AI/ML Engineer | LLMs · RAG · LangGraph · LangChain · FastAPI · Azure | Reduced LLM Token Usage by 99%

About

I'm a Site Reliability Engineer at Smartborn Software Consulting and an AI/ML Engineer with a track record of building production systems that have measurable impact. My focus is writing clean, high-throughput code that handles complex, real-world data processing without inflating infrastructure costs. During my recent engineering tenure, I designed end-to-end AI automation workflows, including a custom semantic caching and vector search layer that reduced LLM token usage by 99% and accelerated API response times by 10x across 15,000+ candidate profiles. I excel at taking raw machine learning theories and deploying them as containerized, production-ready microservices. Core Technical Competencies: • Backend Engineering: Python, FastAPI, Flask, REST APIs, Nginx, Linux Systems, Git • AI & Data Architecture: LLMs, Advanced RAG, LangChain, LangGraph, Qdrant, OpenSearch • Cloud & DevOps: AWS (EC2, ECS, S3, Bedrock), Docker, Automated CI/CD Workflows • Specialized Integrations: Claude API, Model Context Protocol (MCP), deep learning architectures (IEEE submission) I focus on building stable, scalable applications that solve actual system bottlenecks. Always open to discussing system design, backend architectures, or open-source software tools. Let's connect!

Location

Bengaluru

AI stack

aistudio

anthropic apis

antigravity

claude code

claude

codex

Work experience

Site Reliability Engineer at SMARTBORN - CMMI Level 3 Company, Aug 2026 - Sep 2026 · 1 mo, Bangalore, Working as Site Reliability Engineer on an Azure-based ML forecasting platform for weather and power prediction in the wind energy domain. • Investigate and resolve production incidents and contribute to wind-farm platform onboarding • Analyze production issues using application logs and PostgreSQL databases • Build Agentic AI workflows using LangGraph and Azure AI Foundry for operational automation • Work with Azure Service Bus for event-driven multi-agent communication and incident handling

Intern ( AI and Backend) at SMARTBORN - CMMI Level 3 Company, Jul 2026 - Jul 2026 · 1 mo, Built an offline AI Policy Assistant — a fully local, privacy-first RAG system with attribute-based access control. • Reduced database query latency by 99.89% (73.7s → 79ms) by building a semantic intent router that detects query type and routes to the fastest optimized handler • Implemented attribute-based access control (ABAC) for role and demographic-based policy document access restrictions • Built the full RAG pipeline using FastAPI, Qdrant, SQLite, SentenceTransformers, and Ollama with local Llama/Qwen models - fully offline, zero cloud dependency • Optimized document retrieval using semantic caching, smart chunking, and prompt optimization techniques

Associate Developer Intern at Idyllic Services, Jan 2026 - Jun 2026 · 6 mos, Chhatrapati Sambhajinagar, Maharashtra, India, Built production AI systems for JD-driven candidate sourcing and AI-proctored interview automation. • Reduced LLM token usage by 99% (200K → 5K tokens per iteration) by eliminating LLMs from loops and using targeted vector retrieval with semantic caching • Improved API throughput 10x (6 min → 90 sec per pipeline run) through async orchestration and batched processing • Indexed 15,000+ candidate profiles in Qdrant and built a JD-to-candidate matching pipeline using GPT and vector similarity search • Developed an AI-proctored interview platform with real-time speech-to-text, text-to-speech, and face detection • Built REST APIs using FastAPI for backend integration of all AI processing pipelines

Education

Bachelor of Technology - BTech, Information Technology, Government College of Engineering Aurangabad

HSC, Mallik junior college

Public links

github: https://github.com/Rugvedrc

medium: https://medium.com/@Rugvedchandekar

leetcode: https://leetcode.com/rugvedrc

rugved.me: https://rugved.me/