Principal Architect, Autonomous and Knowledge Platform

Our Company

At Teradata, we believe that people thrive when empowered with better information. That's why we built the most complete cloud analytics and data platform for AI. By delivering harmonized data, trusted AI, and faster innovation, we uplift and empower our customers—and our customers' customers—to make better, more confident decisions. The world's top companies across every major industry trust Teradata to improve business performance, enrich customer experiences, and fully integrate data across the enterprise.

What You'll Do

In this role, you will be part of Teradata's Product Engineering leadership team and will lead the architecture for the autonomous and knowledge platform. You will play a pivotal role in driving technical strategy, ensuring the platform's reliability, scalability, and performance across hybrid cloud environments, enabling Teradata to deliver trusted, enterprise-grade solutions.

Responsibilities:

• Launch production-grade functionality in Teradata's Knowledge and Data Platform, driven by agentic AI

• Lead hands-on engineering effort of core developer teams embedding agentic AI into core systems

• Work with knowledge/semantic modeling teams on evolving POC-level agentic AI use cases into production-grade code

• Partner with senior leaders on the vision, state of the art agentic AI and drive this vision into production

• Partner with AI platform engineering teams on company-wide frameworks to launch production-ready agentic AI applications

Who You'll Work With

This role reports directly to the VP, Product Engineering, Autonomous and Knowledge Platform and partners across the Teradata ecosystem. You will:

• Collaborate with engineering, data science, and AI teams to ensure infrastructure and automation strategies support cutting-edge analytics and AI capabilities.

• Partner with the Office of the CTO to align infrastructure and automation roadmaps with Teradata's innovation and technology vision.

• Work closely with Security Engineering to ensure infrastructure and release processes meet enterprise-grade security and compliance requirements.

• Engage with product management and go-to-market teams to understand customer needs and shape infrastructure solutions that enhance Teradata's AI and analytics offerings.

• Support R&D teams in evaluating new tools, technologies, and automation frameworks to drive efficiency and reliability on Teradata's platform.

What Makes You a Qualified Candidate

You bring a rare blend of deep technical expertise, system-level thinking, and strategic leadership.

• 15+ years of experience in enterprise architecture, distributed systems, or large-scale analytics platforms.

• Demonstrated experience integrating AI and ML into enterprise-grade products at scale.

• Expertise in hybrid and multi-cloud architectures, including secure integration with hyperscalers (AWS, Azure, Google Cloud).

• Strong understanding of agentic AI architectures, orchestration frameworks, and generative AI integration.

• Proven track record of building production-grade AI/ML inference pipelines with governance and monitoring.

• Knowledge of open data formats, modern query engines, real-time streaming, and enterprise APIs.

• Experience modernizing platforms from monolith to microservices with Kubernetes-based deployment.

• Master's degree in computer science, Engineering, or related technical discipline (PhD preferred).

What You Will Bring

• A strategic mindset with a hands-on, systems-thinking approach to architecture.

• The ability to lead without direct authority by mentoring and influencing senior engineers across the organization.

• Deep understanding of platform reliability, performance optimization, observability, and secure AI deployment.

• Exceptional communication skills to clearly articulate technical vision and business impact.

• A passion for AI, data, and analytics and a drive to deliver innovation at a global enterprise scale.

Why We Think You'll Love Teradata

We prioritize a people-first culture because we know our people are at the very heart of our success. We embrace a flexible work model because we trust our people to make decisions about how, when, and where they work. We focus on well-being because we care about our people and their ability to thrive both personally and professionally. We are committed to actively working to foster an inclusive environment that celebrates people for all of who they are.