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AI Engineer with 1+ years in RAG pipelines, multi-agent systems, and computer vision
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Assessing your cultural and operational fit
AI/ML Engineer (B.Tech 2026, CGPA 8.3) with 20+ end-to-end production AI projects. IEEE-published researcher (ICSSAS 2026) and hackathon winner. Specialises in RAG pipelines, multi-agent orchestration (LangGraph), and vector search (Qdrant, Pinecone, FAISS). 365-day coding streak, 60+ open-source repositories.
Vignan Institute of Technology and Science
B.Tech · Artificial Intelligence and Machine Learning
August 1, 2023 – June 30, 2026
Government Polytechnic College
Diploma · Mechanical Engineering
August 1, 2020 – June 30, 2023
US-Based Client Project
AI/ML Engineer Intern
May 1, 2025 – July 1, 2025
India
Evoastra Ventures Pvt Ltd
AI Intern
January 1, 2025 – December 31, 2025
India
Indian Legal Intelligence System
June 24, 2026 – Present
• Built a Document Q&A platform mapping criminal and civil scenarios to Indian statutory law with 90%+ precision. • Designed hybrid retrieval combining dense vector search and keyword matching, cutting retrieval latency by 30%.
Math Professor Agent
June 24, 2026 – Present
• Engineered an agentic copilot with intelligent tool routing to autonomously solve multi-step academic queries end-to-end. • Deployed as a Dockerised FastAPI service, maintaining low latency under concurrent user load.
LegalMind AI - Multi-Agent Research System
January 1, 2025 – December 31, 2025
• Architected a multi-agent system using LangGraph orchestrating specialised agents for statutory analysis, citation retrieval, and reasoning synthesis. • Built a high-performance re-ranking retrieval layer using Qdrant, improving citation accuracy by 35% over baseline vector search. • Delivered real-time reasoning traces via a streaming FastAPI backend, enabling interpretable and grounded legal AI outputs.
View ProjectGenerative AI Essentials
Microsoft
June 1, 2026 – Present
Python with ML
Coursera
June 1, 2026 – Present
Python
University of Moratuwa
June 1, 2026 – Present
MSF-UNet: Multi-Scale Flow Guided UNet for Enhanced Semantic Change Detection
IEEE Xplore (ICSSAS 2026)
May 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse academic projects, including legal and academic domains, show adaptability and a broad interest in applying AI to different fields. Their involvement in a hackathon and open-source contributions suggest a proactive and collaborative spirit. The publication in IEEE Xplore indicates a commitment to contributing to the scientific community. The blend of academic rigor and practical application aligns well with a culture that values both research and implementation.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through hackathon wins and complex project architectures. Their 365-day coding streak indicates dedication and a strong work ethic. The ability to document findings for global engineering teams suggests good communication and collaboration potential. The academic projects and publication highlight a research-oriented mindset and a drive for innovation.