专业的 LaTeX 简历模板，专为大模型与 Agent 算法工程师设计 | Professional LaTeX resume template for LLM & Agent algorithm engineers

实战案例：从 0 到 1 搭建 LLM 智能简历筛选 Agent 系统（设计+实现）- code by claude code + kimi

Resume as Code: Your career, managed like a software project. 🚀 Stop manual tailoring. Leverage LLM agents to transform a modular YAML "Master Timeline" into high-impact, STAR-aligned, JD-tailored resumes in minutes. Powered by YAMLResume & AI.

Automated screening agent using Gemini 2.5 Flash to rank resumes via LLM-based gap analysis.

A Model Context Protocol server that gives an LLM agent a persistent, hierarchical task tree scoped by project. The agent decomposes complex goals into sub-tasks, tracks progress, records outputs, handles failures by branching to alternatives, and resumes work across sessions — all without holding the full plan in context.

🎨 An AI Agent Skill for building pixel-perfect A4 PDF resumes | AI Agent 简历生成技能 — Feed raw notes to LLM, get print-ready PDF with smart page-break protection. Works with Antigravity / Cursor / Claude / ChatGPT + Playwright.

A resume agent that allow users to upload a resume, then extract relevant information in JSON format using a LLM, and generate a new formatted resume

Buliding LLM based recruiting Agent where it analyzes resumes and gives feedback to the recruiter about the candidate.

It analyzes your resume, extracts skills, identifies gaps, retrieves learning resources, and generates a personalized study plan powered by an LLM agent, RAG system, and a modern data engineering pipeline.

An app powered by LLM agents that take in a link to a job post and the users' resume as pdf and provide thorough analysis of the resume inlcuding a score for match, probability of passing ATS systems and advice on how to improve resume to tailor it for the provided job description.

Agentic AI-powered HR automation platform built with LangGraph, LLMs, and Python. Instant CV Intelligence for Modern Hiring Teams - AI evaluates resumes in seconds using autonomous AI agents — saving recruiters hours, reducing time. Complete end-to-end code based solution - Fully tested

An automated talent acquisition pipeline designed to streamline candidate screening using Agentic AI. This project uses LLMs to parse resumes and job descriptions, ranking candidates based on semantic alignment, with full observability provided by LangSmith.

In this project, a Streamlit Application with AI Multi-agent workflows has been build in Python for Resume matching of candidates for a given role with Langchain, LangGraph and Llama3 model (Open Source LLM) through Groq.

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An agent that generates tailored cover letters by matching resumes to job descriptions using OpenAI’s LLM and LangChain

ResumeCraft Pro is an advanced AI-powered resume optimization platform that leverages multiple AI agents to transform job applications. The tool takes your existing resume and job description, then uses multiple LLM as agents to analyze, enhance, and cross check the generated latex code of your resume for maximum impact.

This project uses an AI agent to automatically search and apply for jobs on LinkedIn based on a provided resume (PDF). It leverages FastAPI for the backend API, Langchain for agent management, and Playwright (via `browser_use`) for browser automation. The AI agent uses LLM to understand the resume and formulate search queries.

ResumeGenie is an AI Agentic System that streamlines your entire job application process. Powered by LangChain and LangGraph, it orchestrates intelligent agents to scrape the latest remote job listings, filter them based on your preferences, and leverage cutting-edge LLMs (like LLaMA-3 via Groq) to tailor your resume.

Use LLMs to build/parse resume, know about it and change it according to different Job descriptions - also verify the parsign with human in the loop.

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LLM agent for tailoring resume to job description.

AI-powered resume optimization agent using multiple LLMs

AI-powered resume optimizer using multi-agent LLM workflows

Agentic Resume matcher with LLM using NestJS and ReactJS

Using LLM agents to rate resumes based on job descriptions.

Continuous ReAct agent for LLMs with persistent memory and resumable execution

An Agentic RAG pipeline for intelligent resume screening using semantic search and LLM-powered scoring.

CSE585 project - make LLM agents crash-resilient: resume execution from failure and prevent duplicate tool calls.

Use RAG, Agent, LLM to get jobs, analysis resume and job requriements, and apply to the job

This project aims to automate the extraction, cleaning, and enhancement of resume content using Large Language Models (LLMs). The workflow enables LLMs and agents to: - Extract all relevant text from .docx resumes