What You Will Do
In this role, you will be part of Teradata's Product Engineering leadership team and will lead the next gen agentic architecture for AI across Teradata's data and analytics platform. You will be a critical force in defining how Teradata evolves to deliver intelligent, scalable, and secure AI capabilities tightly integrated into our hybrid cloud platform.
Your work will shape the AI architectural direction for Teradata's analytics and applications stack, ensuring that our platform natively supports advanced AI-driven use cases for enterprises. You will design modern, modular solutions across multi-cloud and on-prem environments, integrating agentic AI, generative AI, open data formats, and real-time streaming into Teradata's portfolio. Your leadership will enable Teradata to maintain its position as the most trusted, enterprise-grade data and AI platform in the world.
In this role, you will:
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- Architect Teradata's foundational AI strategy - driving capabilities that enable agentic AI, GenAI, and advanced analytics on the Teradata VantageCloud platform.
- Design scalable, performant AI-driven architectures using open table formats (Iceberg, Delta), query engines (Trino, Presto, Spark), and event streaming (Kafka, Pulsar).
- Integrate AI into Teradata's products, including orchestration, context management, and long-running workflows with frameworks like LangChain, Semantic Kernel, and connectors to Amazon Bedrock, Azure OpenAI, and other ecosystem partners.
- Define reusable patterns for embedding AI/ML inference into customer-facing workloads, with strong emphasis on reliability, explainability, and governance.
- Modernize the platform through microservices, Kubernetes-native deployment, observability, and API-first integration, ensuring AI services are secure, compliant, and enterprise-ready.
- Champion responsible AI at Teradata by building governance frameworks that ensure fairness, transparency, and trust in AI-driven analytics.
- Lead architectural reviews and strategy alignment across engineering teams to drive consistency, scalability, and innovation.
Who You Will Work With
This role reports directly to the SVP, Product Engineering, AI, Analytics, Apps, and UX and partners across the Teradata ecosystem.
You will:
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- Influence and guide engineering, design, and data science teams on AI architecture and delivery strategy.
- Collaborate with the Office of the CTO on innovation, research, and future-state technology roadmaps.
- Partner with Infrastructure and Security Engineering to ensure Teradata's AI services meet enterprise-scale performance and security requirements.
- Engage with customers, partners, and GTM teams to deeply understand enterprise AI use cases and help shape Teradata's AI product roadmap.
- Work with R&D and innovation teams to evaluate emerging AI technologies, run proof-of-concepts, and validate enterprise applicability.
What Makes You a Qualified Candidate
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- 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
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- 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 global enterprise scale.
