AI Engineer with less than a year in Python Backend & GenAI
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Recent B.Tech CSE graduate specializing in Python backend and GenAI engineering. Built and deployed FinSight - a production-grade multi-agent financial intelligence platform (LangGraph, FAISS RAG, Groq LLM) achieving RAGAS scores of 0.8+. Hands-on across the full stack: agentic pipelines, vector databases, REST API design, and Django-based web systems. Strong DSA fundamentals (150+ LeetCode) with system design exposure and internship experience in scalable data architecture. Immediately available for SDE / AI-ML engineering roles.
Shri Vaishnav Vidyapeeth Vishwavidyalaya
B.Tech · Computer Science Engineering
August 1, 2022 – June 30, 2026
Nehru Montessori School
CBSE · Class XII
N/A – Present
Nehru Montessori School
CBSE · Class X
N/A – Present
Infosys Springboard
AI/ML Engineering Intern
October 1, 2025 – December 1, 2025
India
Janmat – Public Grievance Redressal Platform
June 23, 2026 – Present
Architected full-stack civic platform with JWT authentication, REST APIs, and RBAC applying OOP design principles across a multi-tier system. Integrated Leaflet.js for geo-tagged complaint mapping; managed complete grievance lifecycle from submission to resolution, reducing manual reporting dependency.
FinSight - Multi-Agent Financial Intelligence Platform
June 23, 2026 – Present
Architected a 5-agent LangGraph pipeline (retrieval, analysis, summarization, Q&A, evaluation) processing ~1,700 pages of annual reports via FAISS vector search and HuggingFace embeddings. Built RAG-based document intelligence for natural language querying over dense financial filings; achieved RAGAS scores of 0.8+ across faithfulness, answer relevancy, and context precision. Integrated real-time stock data (yfinance) with Groq LLM inference, combining structured and unstructured financial sources in a single production-deployed Streamlit application.
Programming in Java, DSA, DBMS, Soft Skills
NPTEL
June 1, 2026 – Present
Python, Machine Learning, SQL
Kaggle
June 1, 2026 – Present
Virtual Internship – Artificial Intelligence
IBM
March 1, 2026 – Present
Cultural Fit Analysis
The candidate's project portfolio, including a public grievance redressal platform and a financial intelligence platform, demonstrates a diverse interest in applying AI/ML and software engineering to real-world problems. The internship experience and certifications further broaden their skill set, indicating a proactive learning attitude. The combination of backend development, GenAI, and data engineering skills aligns well with the demands of an AI Engineer role, suggesting a good cultural fit for a technically challenging and innovative environment.
Soft Skills & Operational Fit
The candidate's project descriptions highlight an ability to architect complex systems, integrate various technologies, and deliver production-grade applications. This suggests strong problem-solving, analytical, and execution skills. The focus on reducing manual dependencies and improving efficiency in projects indicates a results-oriented approach. The detailed descriptions of project architectures and outcomes demonstrate good technical communication.