Staff AI Engineer

What You’ll Do

As a Staff AI Engineer, you will play a key role in designing and delivering highly scalable, next generation Database products within our Database Marketplace. You will work in a technically rich environment with talented peers, contributing to product strategy, architecture, and execution while influencing the evolution of Teradata’s DB capabilities.

In this role, you will:

• Design, develop, and maintain high-quality systems, services, and applications with an emphasis on scalability, reliability, and performance.

• Collaborate with cross-functional engineers and product partners to shape architecture and consistently deliver end-to-end features.

• Storage layer evolution — Work on page management, durability guarantees, and consistency semantics across disaggregated compute storage topologies.

• Write path and recovery — Extend the logging and recovery subsystem for multi-node and branching workload patterns.

• Concurrency and isolation — Build visibility and isolation semantics for non-linear, multi-context execution patterns.

• Executor-storage interface — Own buffer management, prefetch behavior, and cost model correctness when storage is remote.

• Agentic tooling — Use AI coding agents critically on a large C/C++ codebase. Know where they fail.

Who You’ll Work With

You will be part of a high-performing engineering team building core components of Teradata’s AI platform. You will collaborate closely with other engineers, AI/ML specialists, product managers, cloud architects, and partner teams across the company. The role offers opportunities to contribute directly to Teradata’s AI product roadmap and technological direction.

What Makes You a Qualified Candidate

• Bachelor’s degree in Computer Science or equivalent from a premier institution.

• 3+ years of experience on backend services, distributed systems, or data platform development.

• Strong proficiency in C, C++, Rust for development.

• Preferably Internals experience with PostgreSQL or postgres based relational engine — source-level, not API-level 

• Deep understanding of the WAL write path, checkpointing, and crash recovery mechanics 

• Ability to trace and resolve concurrency anomalies through the engine's MVCC implementation 

• Clear mental model of where traditional storage assumptions live in the executor and buffer manager 

• Practical experience with AI coding assistants on production systems engineering work 

What You’ll Bring

• Expertise in systems or database engineering, with meaningful time spent inside a relational engine at the source level 

• Demonstrated contributions to PostgreSQL or an equivalent open-source engine — patches, extensions, or fork-level work 

• Production experience with storage or replication subsystems under real failure conditions 

• Comfort operating across distributed teams with high autonomy and low process overhead 

• A track record of technical decisions that held up — and the judgment to know when to revisit them