Headline

AI Lead at Tiger analytics | Ex-Infosys | AI Engineer | GenAI RAG and LLM Systems | FastAPI | 2500+ DSA Problems Solved | CodeJam & HackerCup Qualifier | Building Scalable AI for Real-World Impact

About

Experienced AI Engineer | Generative AI | Machine Learning | LLM | RAG | Python | FastAPI | Spring Boot | Java | MLOps | Azure I am an AI Engineer with 2+ years of experience designing and deploying production-grade Generative AI and Machine Learning solutions for large-scale systems. My expertise includes Retrieval-Augmented Generation (RAG), multi-agent AI systems, LLM orchestration, and end-to-end backend development using Python (FastAPI), Java (Spring Boot), and LangChain. 🚀 Key Achievements Built and deployed a multi-agent GenAI framework that automated code generation, reducing latency by 40%. Enhanced RAG precision from 65% → 90% and decreased query latency by 50% using hybrid semantic search. Scaled FastAPI microservices to handle 10,000+ requests/min with Redis caching and GPU optimization, achieving 60% lower latency. 🏆 Technical Strengths Strong command of data structures, algorithms, NLP, deep learning, and system design. Solved 2500+ DSA problems (LeetCode + Codeforces) and qualified for Meta Hacker Cup & Google CodeJam. Skilled in Docker, Kubernetes, MLOps, and cloud deployments on Azure. I’m seeking SDE2 / AI Engineer roles in companies where I can build scalable, intelligent, and high-performance AI products. 📩 Let’s connect to discuss how I can contribute to your next-generation AI initiatives.

Location

Prayagraj

AI stack

claude

gemini

github copilot

langchain

langgraph

ollama

Work experience

Data & AI Lead at Tiger Analytics, Dec 2025 - Present · 11 mos, Bengaluru, Karnataka, India

Specialist programmer at Infosys, Aug 2023 - Nov 2025 · 2 yrs 4 mos, Bengaluru, Karnataka, India, Spearheaded the architecture and deployment of an enterprise-grade, multi-agent system for MuleSoft, automating RAG-to-code generation and reducing system latency by 40%. Optimized RAG system performance, boosting retrieval precision from 65% to 90% and cutting query latency by 50% by implementing an advanced hybrid search (Vector + Cross-Encoder). Scaled a high-throughput FastAPI service to over 10,000 RPM, achieving a 60% latency reduction by implementing Redis caching and GPU acceleration. Deployed a fully autonomous AI support assistant on Azure that resolved 45% of user incidents without human intervention, improving overall incident resolution time by 30%. Engineered a LangGraph-based chatbot for real-time CRUD operations, enhancing data integrity by reducing manual data entry errors by 40%. Developed an end-to-end RAML generation pipeline leveraging Azure Vector Search and text-embedding-ada-002, accelerating API prototyping across 100+ test cases. Automated Confluence reporting for engineering teams, reducing manual documentation effort by 70%.

Specialist programmer intern at Infosys, Feb 2023 - Jul 2023 · 6 mos, Mysore, Karnataka, India, Engineered scalable microservices using Spring Boot and Kubernetes, leading to a 50% improvement in cluster efficiency. Automated Kubernetes workflows utilizing the Java Client library, which reduced manual operational effort by 50% compared to using the kubectl CLI.

Education

Bachelor of Engineering - BE, Computer Science, Sant Longowal Institute of Engineering and Technology

Public links

leetcode: https://leetcode.com/ayus786

codeforces: https://codeforces.com/profile/ayu0809