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AI Engineer with less than a year in LLM development and data science.
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Highly motivated and results-oriented AI Engineer with approximately 6 months of experience in developing and deploying intelligent systems. Proficient in Python, Machine Learning, Generative AI, and full-stack development using Next.js and React.js. Experienced in building AI-powered platforms, optimizing data pipelines, and implementing fraud detection systems. Actively pursuing a B.Tech in Computer Science and Engineering with a strong academic record.
SRM University, Andhra Pradesh
B.Tech · Computer Science and Engineering
August 1, 2022 – June 30, 2026
Ethara AI
LLM Trainee Intern
January 27, 2026 – May 15, 2026
India
Edunet Foundation
Data Science Intern
June 1, 2024 – August 31, 2024
India
Profit-Optimized Fraud Detection Engine
June 5, 2026 – Present
Implemented an end-to-end fraud detection system on highly imbalanced financial transaction data, prioritizing profit optimization and cost-sensitive decision making over accuracy-only metrics. Performed comprehensive EDA and feature engineering to uncover fraud patterns and transaction behavior. Trained and evaluated multiple machine learning models, selecting XGBoost based on ROC-AUC, Precision, and Recall, achieving 91.5% balanced accuracy and 94.4% precision on unseen data. Translated model predictions into measurable business impact by estimating $ 57.25M in net profit, significantly reducing financial losses compared to the existing fraud detection approach.
View ProjectClario - AI Intelligence
June 5, 2026 – Present
Architected and deployed a full-stack SaaS platform using Next.js 14, React 18, and TypeScript, integrating Groq LLM API for real-time operational insights, enabling 40% faster incident identification. Refined a context-aware dashboard with 3 dynamic scenario datasets that adapts based on user queries, processing 100% requests with AI intelligent error handling and exponential fallback retry logic. Built comprehensive API route handlers for query processing and metrics retrieval, processing structured JSON responses with TypeScript type safety throughout the code. Streamlined a 7-agent AI reasoning pipeline processing 100%+ of operational incidents, achieving 99% accuracy in risk management and enabling businesses to manage risk and scale efficiently.
View ProjectLoan Eligibility Engine
June 5, 2026 – Present
Engineered an event driven pipeline with S3 and Lambda to ingest CSVs and store user data in PostgreSQL, processing 100+ records per upload. Designed a 3 stage optimization pipeline combining SQL filtering, business logic, and selective AI to reduce LLM calls by 100%. Automated loan product discovery, matching, and emails through 3 n8n workflows integrated with RDS and AWS SES. Produced 563 validated matches from 1,400 comparisons with 0 AI cost, improving system efficiency and scalability.
View ProjectCultural Fit Analysis
The candidate's project diversity, ranging from full-stack AI platforms to data engineering pipelines and fraud detection systems, indicates a broad interest and adaptability. The involvement in a hackathon and the variety of technologies used suggest a proactive and learning-oriented mindset. The projects align well with an AI Engineer role, demonstrating practical application of AI/ML concepts.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through complex project implementations like the profit-optimized fraud detection engine and the AI reasoning pipeline. Their ability to architect full-stack solutions and integrate various technologies suggests good operational fit for end-to-end development. The internship experience in reviewing AI-generated responses indicates an attention to detail and quality assurance in AI systems.