Senior AI Platform Architect

Teradata; Lincoln (NE); On-site; USD 200,000 - 299,000; Full time

Job summary

Teradata Corporation is seeking a Senior Staff AI Engineer to lead the design, evolution, and scaling of enterprise AI platforms. You will own architecture-level decisions, influence AI platform strategy, and guide initiatives spanning agentic AI, RAG, and vector stores.

The role demands deep expertise in backend services, distributed systems, and production-grade AI systems with SQL/NoSQL data stores, collaborating across product, research, and cloud teams.

Qualifications

• Bachelor's degree or equivalent practical experience in Computer Science, Engineering, or related field.
• 12+ years of experience building backend services, distributed systems, or data/AI platforms.
• Strong proficiency in Java, Go, or Python with experience building largescale services.
• Deep understanding of distributed system design, scalability, fault tolerance, and cloud-native architectures.
• Proven experience designing and operating production systems with SQL and NoSQL data stores.

Responsibilities

• Lead design and evolution of largescale, distributed AI systems powering Teradata's AI platform and products.
• Own end-to-end architecture for agentic workflows, RAG pipelines, vector search, semantic retrieval, and AI orchestration frameworks.
• Drive technical strategy and architectural consistency across multiple engineering teams.

Skills

Java

Go

Python

LLMs

Embeddings

Vector databases

AI orchestration frameworks

Kubernetes

Docker

CI/CD pipelines

Observability

Education

Bachelor's degree in Computer Science, Engineering, or equivalent

Tools

Kubernetes

Docker

CI/CD pipelines

Job description

Teradata Corporation is seeking a Senior Staff AI Engineer to lead the design, evolution, and scaling of enterprise AI platforms. You will own architecture-level decisions, influence AI platform strategy, and guide initiatives spanning agentic AI, RAG, and vector stores.

The role demands deep expertise in backend services, distributed systems, and production-grade AI systems with SQL/NoSQL data stores, collaborating across product, research, and cloud teams.