Senior AI Platform Architect

Teradata; Atlanta (GA); Hybrid; USD 180,000 - 260,000; Full time

Job summary

Teradata is seeking a Staff AI Engineer to lead the architecture and scaling of its enterprise AI platforms. You will design and own critical AI capabilities, collaborating with product and architecture leadership to drive strategic decisions and ensure robust, secure systems.

You will guide multiple engineering teams, implement production-grade AI pipelines, and raise the bar for reliability, governance, and cost control in enterprise AI workloads.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
• 8+ 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.
• Own end-to-end architecture for critical AI capabilities such as agentic workflows, RAG pipelines, vector search, and AI orchestration frameworks.
• Drive technical strategy and architectural consistency across multiple engineering teams.
• Mentor Senior and Staff engineers, guiding architecture reviews and technical decisions.
• Partner with product management and architecture leadership to translate business needs into scalable AI solutions.

Skills

Java

Go

Python

Distributed systems

AI platforms

Cloud architecture

Observability

Backend services

Education

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

Tools

Kubernetes

Docker

CI/CD

SQL

NoSQL

LLMs

Vector databases

Job description

Teradata is seeking a Staff AI Engineer to lead the architecture and scaling of its enterprise AI platforms. You will design and own critical AI capabilities, collaborating with product and architecture leadership to drive strategic decisions and ensure robust, secure systems.

You will guide multiple engineering teams, implement production-grade AI pipelines, and raise the bar for reliability, governance, and cost control in enterprise AI workloads.