AI Solutions Engineer. The role, the market signal, and how to build it in your org.
The pre-sales and post-sales engineer for AI products: runs the demo, builds the pilot on the customer's data, and carries the integration through onboarding. 14 companies posting, heaviest at AI-tooling vendors.
17 postings · 14 distinct titles · from 264,613 real job postings · see the live data →
What the postings ask this role to do
310 tasks extracted from real AI Solutions Engineer job descriptions, classified Automate / Augment / Human-only. Only 1.3% can be fully automated: companies are hiring this role for the judgment, not the keystrokes.
- Use standard ci/cd and environment practices.
- Develop and maintain documentation for ai systems
- Use ai-assisted development tools to accelerate implementation.
- Identify data sources and extract data from diverse environments.
- Support customer success and adoption of the platform.
- Represent the voice of the customer internally.
- Influence the product roadmap based on real-world customer feedback.
- Partner with sales, support, product, and engineering to lead technical success after the sales process.
From the market's version of this role to your version of it
Compose your org's AI Solutions Engineer job description
Start from the tasks real postings ask for, keep the ones that match your operation, add what is specific to you. The tasks carry their AI classification, so the JD you take away already says what AI runs and what stays with people.
Start with the work, not the org chart.
Run the audit on one operation and see what this role would own first.