Career-Ops on Claude

Career-Ops on Claude

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Career-Ops is an AI-powered job search automation system built on Claude Code that evaluates job offers with structured A-F scoring, generates ATS-optimized tailored resumes, scans career portals automatically, and tracks applications through an intelligent pipeline.
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Career-Ops on Claude

Product Information

Updated:Apr 10, 2026

What is Career-Ops on Claude

Career-Ops is an open-source, multi-agent job search system that transforms Claude Code into a comprehensive career management command center. Created by Santiago Fernández de Valderrama, Head of Applied AI, this tool was born from his own job search experience where he evaluated 740+ job listings, generated 100+ personalized CVs, and successfully landed his dream role. Unlike spray-and-pray application tools, Career-Ops functions as an intelligent filter designed to help candidates identify the few truly worthwhile opportunities from hundreds of listings. The system operates with a human-in-the-loop design philosophy where AI analyzes and recommends, but the user always maintains final decision-making authority. Built with 14 operational skill modes, the platform features an A-F scoring system across 10 weighted dimensions, automated portal scanning for 45+ pre-configured companies, batch processing capabilities with parallel workers, PDF generation for ATS-optimized resumes, and a Go-based terminal dashboard for pipeline visualization.

Key Features of Career-Ops on Claude

Career-Ops is an open-source, AI-powered job search automation system built on Claude Code that transforms the job hunting process into a structured pipeline. It evaluates job listings using a comprehensive A-F scoring system across 10 weighted dimensions, generates ATS-optimized tailored resumes for each position, automatically scans 45+ pre-configured career portals, and processes applications in batch mode with parallel workers. The system maintains a single source of truth for tracking applications while providing interview preparation tools, negotiation scripts, and a terminal dashboard for pipeline management. Built with a human-in-the-loop design philosophy, it analyzes and recommends but never auto-submits applications, ensuring users maintain final decision-making control.
Intelligent Job Evaluation System: Automatically scores job offers A-F across 10 weighted dimensions including role match, compensation research, growth potential, and cultural fit. Generates comprehensive 6-block evaluation reports with CV match analysis, level strategy, personalization recommendations, and STAR+Reflection interview stories.
ATS-Optimized PDF Generation: Creates tailored, keyword-injected resumes for each job posting using Space Grotesk and DM Sans design. The system analyzes job descriptions and automatically reorders experience by relevance while injecting relevant keywords to pass applicant tracking systems.
Automated Portal Scanner: Scans 45+ pre-configured companies and 19 search queries across major job boards including Greenhouse, Ashby, Lever, and Wellfound. Uses Playwright to navigate career pages and extract new job postings automatically, covering AI labs, voice AI, enterprise platforms, and automation companies.
Batch Processing with Parallel Workers: Evaluates 10+ job offers simultaneously using independent Claude Code sub-agents with 200K context each. Features fault-tolerant architecture with queue management, progress tracking, result merging, and resumable processing with lock files to prevent double execution.
Terminal Dashboard TUI: Provides a Go-based terminal user interface with 6 filter tabs, 4 sort modes, grouped/flat view options, lazy-loaded previews, and inline status changes. Built with Bubble Tea and Lipgloss using Catppuccin Mocha theme for visual pipeline management.
Interview & Negotiation Tools: Accumulates a master bank of STAR+Reflection stories across evaluations, generates salary negotiation frameworks with geographic discount pushback strategies, and provides competing offer leverage scripts tailored to each opportunity.

Use Cases of Career-Ops on Claude

AI/ML Engineering Job Search: Evaluate hundreds of positions across AI labs (Anthropic, OpenAI, Mistral) and LLMOps platforms (Langfuse, Weights & Biases) with specialized scoring for technical depth, research opportunities, and model access. The system classifies roles into archetypes like LLMOps, Agentic AI, and Applied AI to match specific career trajectories.
Executive Role Transition: Filter and evaluate senior leadership positions (Head of, VP, Director level) with emphasis on strategic impact, team size, budget authority, and transformation opportunities. Generate executive-level CVs that highlight leadership experience and business outcomes rather than technical implementations.
Career Pivot Management: Systematically evaluate opportunities in adjacent fields by customizing archetype tables and scoring weights. The system helps identify transferable skills, gaps to address, and positions that bridge current experience with target roles while generating tailored resumes that reframe experience for new contexts.
Remote Work Optimization: Scan specialized remote job boards and filter opportunities by location flexibility, timezone requirements, and remote-first culture indicators. Batch process remote-specific portals like RemoteFront while evaluating compensation with geographic discount awareness and negotiation strategies.
Startup vs Enterprise Strategy: Simultaneously track opportunities across startup ecosystems (n8n, Retool, Vercel) and enterprise organizations (Salesforce, Twilio, Genesys) with customized evaluation criteria for risk tolerance, equity potential, stability preferences, and growth stage alignment.
Portfolio-Driven Application: Integrate proof points from article-digest.md and portfolio projects to automatically inject relevant case studies into each application. The system cross-references job requirements with demonstrated competencies from published work, generating contextualized CVs that link to specific portfolio pieces.

Pros

Human-in-the-loop design ensures users maintain control and never auto-submits applications, reducing spam risk and maintaining professional reputation
Highly customizable through Claude Code itself - users can ask Claude to modify modes, archetypes, scoring weights, and templates without manual file editing
Comprehensive evaluation goes beyond keyword matching by reasoning about CV fit versus job requirements, providing strategic insights for interview preparation and negotiation
Open-source and local-first architecture keeps all personal data on user's machine with no external data collection or hosted service dependencies

Cons

Steep initial learning curve as the system requires substantial context feeding (CV, career story, proof points, preferences) before evaluations become accurate
Requires technical setup including Claude Code, Node.js, Playwright, and optionally Go for the dashboard, which may be challenging for non-technical users
Built specifically for the creator's AI/automation career search, so archetypes, scoring logic, and templates reflect that bias and require customization for other industries
AI model unpredictability means evaluations may hallucinate skills or experience, requiring careful human review before any application submission

How to Use Career-Ops on Claude

1. Install Prerequisites: Ensure you have Node.js, npm, and Git installed on your machine. You'll also need access to Claude Code (Anthropic's AI coding assistant).
2. Clone the Repository: Open your terminal and run: git clone https://github.com/santifer/career-ops.git
3. Navigate to Project Directory: Change into the career-ops directory: cd career-ops
4. Install Dependencies: Run npm install to install all required Node.js packages.
5. Install Playwright Chromium: Run npx playwright install chromium - this is required for PDF generation and web scraping.
6. Verify Setup: Run npm run doctor to validate that all prerequisites are properly installed and configured.
7. Configure Your Profile: Copy the example profile: cp config/profile.example.yml config/profile.yml, then edit config/profile.yml with your personal details, career preferences, and job search criteria.
8. Configure Portal Scanner: Copy the portals template: cp templates/portals.example.yml portals.yml, then customize portals.yml with the companies and job boards you want to scan.
9. Add Your CV: Create a file named cv.md in the project root directory and paste your CV content in Markdown format.
10. Open Claude Code: Launch Claude Code in the career-ops directory by running: claude
11. Personalize the System with Claude: Ask Claude to customize the system for you. Examples: 'Change the archetypes to backend engineering roles', 'Translate the modes to English', 'Add these 5 companies to portals.yml', or 'Update my profile with this CV I'm pasting'.
12. Start Using Career-Ops: Type /career-ops in Claude Code to see all available commands, or simply paste a job URL or job description directly into Claude - it will auto-detect and run the full evaluation pipeline.
13. Evaluate a Job Posting: Paste a job URL or description into Claude. Career-ops will automatically classify the role, evaluate it against your CV with an A-F score across 10 dimensions, generate a tailored PDF resume, and add it to your tracker.
14. Scan Job Portals: Run /career-ops scan to automatically scan the career portals you configured in portals.yml for new job postings matching your criteria.
15. Generate Tailored Resume: Run /career-ops pdf for a specific job to generate an ATS-optimized PDF resume customized with keywords and experience relevant to that job description.
16. Batch Process Multiple Jobs: Run /career-ops batch to evaluate multiple job offers in parallel using sub-agents, allowing you to process 10+ offers efficiently.
17. Track Applications: Run /career-ops tracker to view your application pipeline status, or use the Go dashboard by running: cd dashboard && go build -o career-dashboard . && ./career-dashboard --path ..
18. Review and Refine: Review the evaluation reports in the reports/ directory and generated PDFs in the output/ directory. The first evaluations won't be perfect - feed Claude more context about your career story, preferences, and proof points to improve accuracy.
19. Apply to Jobs (Manual): Career-ops never auto-submits applications. Review the AI-generated evaluation and tailored resume, then manually submit applications for jobs scoring 4.0/5 or higher that align with your goals.
20. Iterate and Improve: Continue using the system, providing feedback to Claude about what works and what doesn't. Ask Claude to adjust scoring weights, archetypes, or evaluation criteria based on your experience.

Career-Ops on Claude FAQs

Career-Ops is an AI-powered job search system built on Claude Code that automates job evaluation and application tracking. It uses Playwright to navigate career pages, evaluates job fit by reasoning about your CV versus job descriptions (not keyword matching), generates tailored ATS-optimized PDF resumes per listing, and tracks everything in a structured pipeline with A-F scoring across 10 weighted dimensions.

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