Principal Architect

Principal AI Architect

What Youll Do

As the Principal AI Architect for Teradata AI Studio, you will define the technical architecture of Teradata's end-to-end AI development environment the platform where data scientists, ML engineers, and AI developers build, test, deploy, and monitor AI and agentic applications on top of Vantage.

You will set the architectural direction for how AI Studio integrates with Teradata Vantage's query engine, model registry, feature store, and agent harness. You will establish the patterns for how enterprise customers build trustworthy AI workflows from data preparation through model deployment to agent-driven automation and ensure that AI Studio is the most capable, governed, and scalable AI development environment in the market.

This is a hands-on technical leadership role. Success means shipping architectural decisions that other engineers can build on with confidence, customers adopting AI Studio at scale, and Teradata being recognized as the platform of choice for enterprise AI development.

Who Youll Work With

You will be the senior technical voice for AI Studio within Teradata's AI Apps, Analytics, and UX Engineering organization. You will partner with the VP of Engineering for AI Platform, the Staff AI Engineers building AI Studio components, and the Product Management team to align architecture with product strategy.

This role has significant cross-functional reach you will engage with Teradata's Core Data Platform team on Vantage integration points, with the Security and Governance team on enterprise-grade AI controls, and with key customers in design partner engagements to ensure AI Studio solves real problems at enterprise scale.

What Makes You a Qualified Candidate

• 10+ years of software engineering experience, including 3+ years in a senior architect or principal engineer role with platform-wide technical scope.
• Demonstrated expertise designing AI/ML platforms or developer tools: model serving infrastructure, feature stores, experiment tracking, MLOps pipelines, or AI agent development environments.
• Deep understanding of LLM integration patterns: RAG architectures, fine-tuning pipelines, evaluation frameworks, and agent tool-calling interfaces.
• Experience with enterprise data platforms (Teradata Vantage, Snowflake, Databricks, or equivalent) at sufficient depth to architect against their APIs, security models, and performance characteristics.

What Youll Bring

• Experience building developer-facing platforms SDKs, APIs, or IDEs that external developers adopt and extend.
• Familiarity with open-source AI development tools: MLflow, Weights & Biases, Hugging Face, LangChain, LangGraph, or comparable.
• Understanding of enterprise AI governance requirements: model lineage, data access controls, audit logging, and responsible AI guardrails.
• Experience with cloud-native architecture (AWS, Azure, GCP) and containerized ML workloads (Kubernetes, Docker).
• Strong cross-functional influence: you can drive alignment across engineering, product, and customer-facing teams without formal authority.
• A portfolio of architectural decisions RFCs, design docs, or open-source work that demonstrates your approach.
• A passion for how AI can unlock potential to help our teams, our customers, and our communities achieve great things.