Applied AI Architect / Engineer. The role, the market signal, and how to build it in your org.
Bridges model labs and customers. Most visible at Anthropic, OpenAI, and frontier-AI partner ecosystems. Translates LLM capabilities into customer-specific solutions.
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.
164 postings · 134 distinct titles · from 264,613 real job postings · see the live data →
What the postings ask this role to do
3,078 tasks extracted from real Applied AI Architect / Engineer job descriptions, classified Automate / Augment / Human-only. Only 0.9% can be fully automated: companies are hiring this role for the judgment, not the keystrokes.
- Produce progress reporting.
- Identify common integration patterns
- Apply secure coding practices to mitigate vulnerabilities.
- Stay informed of industry technology trends and innovations.
- Identify common integration patterns and contribute insights back to product and engineering teams.
- Help customers develop evaluation frameworks to measure claude's performance for their specific use cases.
- Contribute deployment insights back to product and engineering teams.
- Coordinate internally across multiple teams and stakeholders to drive customer success
- Collaborate with researchers, ai engineers, and product engineers on complex customer projects.
- Drive technological transformation with customers
- Travel to customer sites to build in person with customers.
- Travel to customer sites for workshops, technical deep dives, and relationship building
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 own, then connect those responsibilities to practice and assessment.