This free AI Solutions Architect job description template is ready to use — copy it, replace the {{placeholders}}, and post your role in minutes. It includes a company intro, a role summary, responsibilities, requirements, nice-to-haves, and compensation, with writing tips and FAQs below to help you tailor it to your team.
When to use this template
Use this when you're hiring a customer-facing technical expert to design AI solutions — scoping use cases, architecting integrations, and guiding customers from idea to deployment. It blends solutions engineering with applied AI depth.
AI solutions architect candidates want to know how technical the customers and product are, whether the role is pre-sales, post-sale, or both, and how it partners with sales and engineering. Be specific.
If the role is general technical pre-sales, use the Solutions Engineer template; if it's internal AI building, use the AI Engineer template.
Writing tips
- Clarify whether the role is pre-sales, post-sale delivery, or both.
- Describe how technical the customers and the AI product are.
- Explain how the role partners with sales, engineering, and customers.
- Balance AI depth with the communication skills to advise customers.
- Include the base salary and any variable or OTE.
The job description
Copy the template below and replace the {{placeholders}} and [bracketed notes] with your specifics.
About {{company}}
{{company}} is [what you sell and to whom]. Our AI product is powerful but takes expertise to apply well, and we're hiring an AI Solutions Architect to help customers succeed with it.
The role
As an AI Solutions Architect, you'll be the technical expert who helps customers design and deploy AI solutions — scoping use cases, architecting integrations, and guiding them from proof of concept to production. You'll partner closely with sales and engineering. This role reports to {{hiring_manager}} and is based {{work_type}} in {{location}}.
What you'll do
- Scope customer use cases and design AI solutions that fit.
- Architect integrations and guide proofs of concept to production.
- Be the trusted technical advisor on AI for customers and prospects.
- Partner with sales on technical discovery and deals.
- Feed customer needs and gaps back to product and engineering.
What we're looking for
- 4+ years in solutions architecture, solutions engineering, or applied AI.
- A strong grasp of modern AI and how to apply it to real problems.
- Excellent communication — you can advise both engineers and executives.
- Hands-on technical ability to design and prototype solutions.
- A genuine focus on solving customer problems.
Nice to have
- A software engineering or data science background.
- Experience selling or deploying AI products.
- Familiarity with [your platform, models, and integrations].
What we offer
- Base salary {{salary_range}}, plus any variable and equity.
- [Comprehensive benefits].
- Flexible {{work_type}} working and [PTO policy].
- A frontier product and customers eager to apply it.
How to personalize
Replace these placeholders before posting:
- {{company}}
- {{location}}
- {{work_type}}
- {{salary_range}}
- {{hiring_manager}}
The bracketed notes — like [your benefits] or [your primary language(s)] — are prompts to swap in your own details. The more specific you are about the actual work and stack, the stronger your applicant pool will be.
Frequently asked questions
- What does an AI Solutions Architect do?
- An AI Solutions Architect is a customer-facing technical expert who designs and guides AI solutions. They scope use cases, architect integrations, lead proofs of concept, and advise customers from idea to production — partnering with sales and engineering to make AI deployments succeed.
- What's the difference between an AI Solutions Architect and a Solutions Engineer?
- A Solutions Engineer is a general technical partner in the sales process across a product. An AI Solutions Architect specializes in AI — designing solutions that account for models, data, evaluation, and the realities of deploying AI. The architect role usually carries more design and post-sale depth.
- What skills should an AI Solutions Architect have?
- A strong grasp of modern AI and how to apply it, hands-on technical ability to design and prototype solutions, and excellent communication to advise both engineers and executives. A software engineering or data science background and experience deploying AI products are valuable.