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AI Engineer with less than a year in LLM-powered applications & RAG pipelines
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Applied AI and Generative AI-focused Computer Science student with hands-on experience building LLM-powered applications, RAG pipelines, AI agents, semantic search systems, and Python backend APIs. Skilled in Python, LangChain, OpenAI API, FastAPI, vector databases, embeddings, prompt engineering, tool calling, and retrieval workflows. Experienced in designing modular AI systems that combine retrieval, reasoning, API integration, automation, and structured output generation for real-world use cases.
Shridevi Institute of Engineering and Technology, Tumkur
Bachelor of Engineering · Computer Science and Engineering
January 1, 2022 – January 1, 2026
Asset Telematics Pvt Ltd
Python Intern
January 1, 2026 – Present
Bangalore Urban, Karnataka, India
Agentic AI Assistant with RAG, MCP, Tool Calling, and FastAPI
January 1, 2026 – Present
Built an AI assistant using LangChain, OpenAI API, RAG, MCP, tool calling, and FastAPI for modular AI task execution. Implemented retrieval-augmented generation using embeddings and vector search to ground LLM responses in relevant context. Designed agentic workflows for multi-step reasoning, prompt routing, tool selection, and dynamic task execution. Integrated conversation memory and structured prompt handling to improve multi-turn interaction quality. Exposed AI workflows through FastAPI endpoints for real-time backend integration and scalable API usage.
Hybrid Trading Intelligence System using SMC, Algorithmic Logic, and LLM Reasoning
January 1, 2026 – Present
Built a hybrid market analysis system combining deterministic Smart Money Concepts logic with LLM-based reasoning. Implemented rule-based detection for market structure, liquidity zones, break of structure, and order blocks using OHLC data. Used LLM APIs to generate contextual market bias, explain detected patterns, and support probabilistic decision-making. Processed and analyzed market data using Python, Pandas, and NumPy for signal detection and structured market commentary.
Web Search Automation and Link Crawler Tool
January 1, 2026 – Present
Developed an automated search and crawling tool for query execution, recursive link extraction, and structured data collection. Used Selenium and BeautifulSoup to handle browser automation, dynamic pages, HTML parsing, and reusable extraction workflows. Built automation scripts for scalable web discovery, link analysis, and data collection from public web pages.
AWS Cloud Practitioner
DataCamp
June 1, 2026 – Present
AI Engineer for Developers Associate
DataCamp
June 1, 2026 – Present
Ethical Hacking and Penetration Testing
Udemy
June 1, 2026 – Present
Generative AI Professional
Oracle
June 1, 2026 – Present
Intermediate Python
Udacity
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's profile shows a strong alignment with an AI Engineer role, given the focus on Generative AI, LLMs, and AI agents in both projects and internship experience. The breadth of technical skills, including various LLM APIs, vector search technologies, and backend frameworks, suggests a versatile individual. The personal projects demonstrate initiative and a passion for applying AI concepts to real-world problems, which is a positive indicator for cultural fit in an innovative and fast-paced environment. The certifications further reinforce a commitment to continuous learning and staying current with industry trends.
Soft Skills & Operational Fit
The candidate's project descriptions and internship experience suggest a proactive and hands-on approach to problem-solving. The focus on building practical AI applications and backend workflows indicates an operational fit for roles requiring implementation and deployment. The diversity of projects (AI assistant, trading system, web crawler) shows adaptability and a willingness to tackle different problem domains. However, without specific psychometric or English test scores, it's difficult to assess communication clarity, logical reasoning, work attitude, stress handling, or team collaboration beyond what's inferred from the resume's content quality.