AI Solutions Engineer. The role, the market signal, and how to build it in your org.
Helps customers evaluate and implement an AI product. Runs demonstrations, builds bounded pilots with approved data and tools, and works with the receiving team through integration and onboarding.
In a workforce of people and AI agents, this role takes shape around the workflows it supports. Define its responsibilities and handoffs, then prepare people to perform that work.
Source snapshot 2026-07-17. Postings do not confirm that a vacancy is still open.
17 postings · 14 distinct titles · from 264,613 real job postings · see the source snapshot →
What the postings ask this role to do
310 tasks extracted from real AI Solutions Engineer job descriptions, classified Automate / Augment / Human-only. In this source classification, 1.3% of task statements are automation candidates. The share does not measure working time or demonstrated agent performance.
- 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
Start with the work, not the org chart.
Define what this role will build, configure, decide and check. Connect that work to an enterprise-specific project and agreed assessment evidence.