AI Solutions Architect
United States of America, Eagan, MinnesotaAll locationsUnited States of America, Eagan, MinnesotaUnited States of America, New York, New York Remote
$100,100 a yearJobFig found this opening at its original source and checks that it remains available.
About the role
As an AI Solutions Architect , you will help law firm customers transform how legal work gets done with Thomson Reuters Legal AI. Combining legal-practice experience, product expertise, and a practical understanding of AI, you will identify high-value legal workflows, design and test AI-enabled solutions, and help customers move successful use cases into sustained adoption. Working closely with Customer Success Managers, you will support adoption across customer organizations, with a particular focus on enabling high-value users and scaling successful workflows. Travel: This role requires regular travel (approximately 25-30%, varying by quarter) to customer and firm sites to support client engagements, demonstrations, and team initiatives.
What you'll bring
- Candidates must be willing and able to travel as a condition of employment.
- You are a fit for the role of AI Solutions Architect if you have the following required qualifications:
- J.D. from an accredited US law school required.
- Prior experience practicing law required (e.g., in a law firm, in-house legal department, government, clerkship, or comparable legal practice setting).
- Proven experience in customer- or client-facing roles
- Familiarity with legal workflows and processes such as due diligence, eDiscovery, large document review, compliance, or related domains — gained through direct practice, adjacent roles, or working with legal professionals.
- Demonstrable experience with generative artificial intelligence applications.
- Substantial experience using a variety of online legal research and practice tools (e.g. Westlaw, Practical Law, HighQ, Relativity, Everlaw, etc.).
- Tech-savvy with a strong aptitude for learning new AI tools and platforms
- no formal technical or programming background is required.
- Bring experience in customer-facing roles
- Understand the architecture and operation of large language models (LLMs) and are comfortable working hands-on with AI tools, even without a formal technical or engineering background.