This repository offers a data-driven field guide to AI engineering roles, skills, and interview practices, synthesizing insights from over 1,765 job descriptions and real-world interview experiences. It targets professionals seeking to understand the AI engineering job market, prepare for technical interviews, and navigate career transitions with practical, data-backed guidance.

How It Works

The project empirically analyzes real-world data, including 1,765 job descriptions and 5,694+ responsibilities, to identify patterns in AI engineering roles, required skills, common use cases, and interview processes. This approach contrasts with AI-generated content, providing synthesized, actionable insights derived directly from industry data and practitioner experiences.

Quick Start & Requirements

Access to the repository's content via GitHub is the primary method; no specific installation or runtime environment is required to consume the information. Relevant resources include:

• Newsletter: Alexey on Data
• Webinars: Scheduled events on AI engineering careers (March 2026)
• Paid course: AI Engineering Buildcamp

Highlighted Details

• Analysis of 1,765 job descriptions and 5,694+ responsibilities, covering roles, skills, and use cases.
• Detailed interview preparation guides for theory, coding, case studies, AI system design, and take-home assignments.
• Company-specific data for 51 companies detailing their interview processes.
• Curated resources include practitioner interview stories, AI system design frameworks, and company engineering blogs.
• Structured learning paths for transitioning into AI engineering from related technical roles.

Maintenance & Community

The repository is actively maintained by Alexey Grigorev, with ongoing content additions and a welcome for community feedback and contributions. Updates are shared via a newsletter, and scheduled webinars indicate active engagement.

Licensing & Compatibility

No explicit open-source license is mentioned in the provided README text. This lack of clarity may pose compatibility issues for commercial use or integration into proprietary projects.

Limitations & Caveats

Key sections like AI system design and behavioral questions are marked as "work in progress." Salary analysis is "Coming Soon." The data reflects trends from Q4 2025 / Q1 2026, potentially missing the most immediate shifts in the rapidly evolving AI engineering field.