Principal AI Architect - Lifescience
Uipath
| Company | Uipath |
| Category | Data & Analytics |
| Location | Remote |
| Remote | Remote |
| Employment | Not stated |
| Level | Lead |
| Salary | Not stated by the employer |
| Posted | 14 Jul 2026 |
| Last verified | 3 Aug 2026 |
| Source | Employer ATS (ashby) |
Description
LIFE AT UIPATH
The people at UiPath believe in the transformative power of automation to change how the world works. We’re committed to creating category-leading enterprise software that unleashes that power.
To make that happen, we need people who are curious, self-propelled, generous, and genuine. People who love being part of a fast-moving, fast-thinking growth company. And people who care—about each other, about UiPath, and about our larger purpose.
Could that be you?
YOUR MISSION
At UiPath, we believe the future of enterprise transformation lies in the convergence of AI, automation, agents, people, and enterprise systems. As a Principal AI Architect, you will serve as a senior strategic advisor to technology and business leaders navigating the rapidly evolving landscape of enterprise AI, agentic systems, automation, and digital transformation. You will help global life sciences organizations define AI strategies, evaluate emerging technologies, establish governance models, and build scalable operating frameworks that accelerate innovation while maintaining control and compliance.
This role combines enterprise technology strategy, executive engagement, industry expertise, and thought leadership. Working directly with CIOs, CTOs, Chief AI Officers, Enterprise Architects, and digital transformation leaders, you will help shape how organizations operationalize AI and Agentic Automation at enterprise scale.
WHAT YOU'LL DO AT UIPATH
- Serve as a trusted advisor to executive leaders on enterprise AI, automation, agentic transformation, and technology strategy.
- Lead strategic discussions with CIOs, CTOs, Chief AI Officers, Enterprise Architects, and digital transformation leaders.
- Help customers define long-term AI, automation, and agentic transformation roadmaps aligned to business, operational, and innovation objectives.
- Understand how organizations are building AI platforms, agent frameworks, copilots, knowledge architectures, orchestration layers, and governance models.
- Articulate how UiPath fits within broader enterprise AI ecosystems and how Agentic Automation complements existing investments in AI, cloud, and enterprise technologies.
- Guide customers through critical architecture decisions including agents versus workflows versus automation, centralized versus decentralized AI models, and governance and control frameworks.
- Develop future-state architecture and operating model recommendations that support scalable and sustainable enterprise AI adoption.
- Advise customers on AI governance, risk management, compliance, security, and operationalization strategies.
- Translate emerging developments in AI, automation, large language models, and agentic technologies into practical business opportunities and transformation initiatives.
- Partner with internal Product, Go-To-Market, Technology Alliances, and Industry teams to ensure that our solutions are comprehensive and match the needs of our customers.
- Represent UiPath as a thought leader through executive briefings, customer engagements, industry conferences, and market-facing events.
- Share industry trends, best practices, and competitive insights across the UiPath organization.
WHAT YOU'LL BRING TO THE TEAM
- Extensive experience advising large enterprises on AI adoption, platform strategy, automation, or technology modernization initiatives.
- Strong understanding of enterprise AI ecosystems, including AI platforms, cloud services, agent frameworks, orchestration technologies, workflow platforms, and automation solutions.
- Ability to evaluate competing and complementary technologies and provide strategic guidance on architecture, operating models, and platform investments.
- Experience helping organizations establish AI governance frameworks, operating models, and enterprise adoption strategies.
- Strong understanding of how enterprises operationalize AI at scale, including platform management, organizatio