Senior AI Platform Architect — Enterprise Systems

Teradata; Boston (MA); On-site; USD 200,000 - 299,000; Full time

Benefits offered by this job

Flexible work model

Inclusive environment

Job summary

Teradata is seeking a Senior Staff AI Engineer to design, evolve, and scale enterprise AI platforms. The role will own architecture-level decisions, influence AI platform strategy, and lead cross-team initiatives spanning RAG, vector stores, LLMs, and agent-based AI systems.

You will work with product and architecture leadership to raise the technical bar, ensuring reliable and cost-efficient AI services across the software development lifecycle.

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 agentic workflows, RAG pipelines, vector search, and AI orchestration frameworks.
• Define and implement guardrails for reliability, safety, governance, and cost control in enterprise AI systems.
• Partner with product management, architecture, and cloud platform teams to translate requirements into scalable AI solutions.
• Mentor senior engineers and raise the engineering bar through design reviews and forums.

Skills

Java

Go

Python

Distributed systems

SQL/NoSQL

Education

Bachelor’s degree in CS or Engineering

Tools

Kubernetes

Docker

CI/CD

Observability

Job description

Teradata is seeking a Senior Staff AI Engineer to design, evolve, and scale enterprise AI platforms. The role will own architecture-level decisions, influence AI platform strategy, and lead cross-team initiatives spanning RAG, vector stores, LLMs, and agent-based AI systems.

You will work with product and architecture leadership to raise the technical bar, ensuring reliable and cost-efficient AI services across the software development lifecycle.