I’m an AI Engineer focused on building production-grade LLM applications, agentic AI, and multi-agent systems. I work across the full stack of AI engineering—designing agent workflows, implementing RAG and semantic search, and deploying scalable backends with FastAPI and Python using the OpenAI API and frameworks like LangChain and CrewAI.
I enjoy optimizing real-world pipelines for reliability and performance, including building fault-tolerant microservices and long-term vector memory solutions. My goal is to turn complex AI requirements into modular, maintainable enterprise features that reduce manual effort and inference latency while supporting strong model evaluation and deployment cycles.
Experience Level
Language
Work Experience
Education
Qualifications
Industry Experience
Developed a full-stack AI-powered proctoring platform ensuring academic integrity for remote examinations.
▸ Implemented real-time face recognition, gaze tracking, and motion detection using OpenCV and deep learning models to monitor student behavior during live exams
▸ Reduced cheating incidents by 30% through automated anomaly detection and instant alert generation
▸ Built React frontend with live video monitoring dashboard and Flask backend with RESTful APIs
▸ Integrated AWS S3 for secure media storage and Firebase for real-time event notifications
▸ Deployed on AWS with auto-scaling capabilities, improving system reliability and supporting concurrent users
Built an intelligent resume screening engine that automates candidate evaluation using semantic AI.
▸ Engineered a multi-stage parsing pipeline using GPT-based LLMs, spaCy NLP, and FAISS vector search to extract and semantically match skills, experience, and qualifications from PDF/DOCX resumes
▸ Implemented relevance scoring algorithm that ranks candidates against job descriptions with high accuracy
▸ Reduced manual recruiter screening time by 70% through automated ranking and skill-gap identification
▸ Designed a clean REST API interface via FastAPI for easy integration into existing HR workflows
Developed a context-aware conversational AI system for conducting intelligent, dynamic surveys.
▸ Built using OpenAI API and LangChain to deliver smooth, multi-turn survey conversations that adapt based on user responses
▸ Achieved 65% increase in user engagement compared to traditional static survey forms
▸ Designed conversation flows that handle edge cases, ambiguous answers, and topic branching intelligently
▸ Integrated response storage and analytics pipeline for post-survey insight generation
Built a fully autonomous multi-agent AI system capable of end-to-end task execution without human intervention.
▸ Designed a scalable multi-agent architecture using FastAPI, CrewAI, and OpenAI GPT-4, enabling agents to plan, reason, and collaborate autonomously
▸ Integrated long-term memory via ChromaDB, allowing the assistant to retain and recall context across sessions
▸ Built modular tool integrations: web search, PDF/document parsing, data analysis, email automation, and file generation
▸ Implemented microservice-based design for low-latency inference, fault tolerance, and independent agent scaling
▸ Supports fully context-aware responses for complex, multi-step real-world tasks.
Hire a AI Engineer
We have the best ai engineer experts on Twine. Hire a ai engineer in Delhi today.