Thomson Reuters
Director, Technology Partner Architecture Solutions – Legal
$158K–$292K
United States of America, Eagan, Minnesota · Remote · Director · Full-time · Posted Oct 20, 2026
- Experience
- 12+ years in solutions architecture, software engineering, or technical consulting, including at least five years leading architecture for enterprise software or platform partnerships.
About the job
Leads architecture and delivery quality for partner-integrated legal technology solutions, combining Thomson Reuters offerings with partner platforms.
What you'll do
- Define and approve solution architectures, integration patterns, and security and privacy controls for partner offerings.
- Lead technical due diligence, customer discovery, proofs of concept, and cross-functional alignment with Product, Engineering, Sales, and Partnerships.
- Lead and develop the solutions architecture team, and monitor partner solution performance and escalations.
What they ask for
- Hands-on experience designing integrations with partner APIs, cloud platforms, and enterprise data systems.
- Experience designing AI or machine learning enabled solutions, including retrieval, model integration, and evaluation approaches.
- Track record translating technical designs into commercial offerings with Product, Sales, and Partnerships teams.
- Experience leading and developing a team of technical professionals; strong knowledge of security, privacy, and compliance for confidential client and legal information.
Nice to have
- Experience in legal technology, legal publishing, or professional services software; presales experience or familiarity with legal workflows.
- Experience with cloud and AI ecosystem partner programs (e.g., AWS, Google Cloud, Anthropic); a law degree or equivalent legal industry experience, or an advanced degree in computer science or engineering.
Pay
$157,500 USD - $292,500 USD (base salary)
Tools
partner APIs, cloud platforms, enterprise data systems, AI, machine learning, AWS, Google Cloud, Anthropic
AI focus
Design AI- or machine-learning-enabled partner solutions, assess partner AI models and governance, and develop retrieval, model integration, and evaluation approaches.
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