Senior Staff AI Architect & Platform Lead

Teradata Corporation (SE); Lansing (MI); On-site; USD 200,000 - 299,000; Full time

Benefits offered by this job

Flexible work model

Job summary

Teradata is seeking a Senior Staff AI Engineer to design, evolve, and scale enterprise AI platforms. You will own architecture decisions, influence platform strategy, and lead complex initiatives spanning agentic AI, RAG, vector stores, and developer AI systems.

You will mentor engineers, collaborate with product and architecture leadership, and raise the technical bar across teams while ensuring reliability and cost discipline.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
• 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 the design and evolution of largescale, distributed AI systems powering Teradata’s AI platform and products.
• Own end-to-end architecture for AI capabilities like agentic workflows, RAG pipelines, vector search, and AI orchestration frameworks.
• Drive technical strategy and architectural consistency across multiple engineering teams.

Skills

Java

Go

Python

Distributed systems

Backend services

Education

Bachelor's degree in CS/Engineering

Tools

SQL

NoSQL

Kubernetes

Docker

Cloud-native

Job description

Teradata is seeking a Senior Staff AI Engineer to design, evolve, and scale enterprise AI platforms. You will own architecture decisions, influence platform strategy, and lead complex initiatives spanning agentic AI, RAG, vector stores, and developer AI systems.

You will mentor engineers, collaborate with product and architecture leadership, and raise the technical bar across teams while ensuring reliability and cost discipline.