Backend Software Engineer (Evals)

OpenAI
San Francisco / Seattle2025-12-23

About the job

We’re looking for a Backend Software Engineer with experience working in ML/LLM-heavy domains to help to design and build an evals infrastructure that measures the quality of OpenAI’s support automation. This is a deeply technical and highly cross-functional role where you’ll build robust systems and backend services that serve as the foundation for how knowledge is created, accessed, and applied across OpenAI. The role will especially focus on working closely with Data Science and Research partners to design and build evals at scale.

Responsibilities

Design eval pipelines that are reliable, reproducible, and extendable

Build the infrastructure for continuous eval monitoring frameworks (regression/drift monitoring, building robust golden datasets) along with feedback loops that ultimately strengthen support automation

Design, build, and maintain backend services and APIs to support intelligent automation and knowledge systems

Integrate and structure data across internal platforms, transforming it into formats optimized for use by downstream systems and AI workflows.

Collaborate closely with data, research, and engineering teams to integrate OpenAI models into high-leverage workflows

Own the full development lifecycle of new backend systems and internal platform capabilities

Build with scale and maintainability in mind, while rapidly iterating on new ideas

Qualifications

Minimum

4+ years of backend engineering experience at product-driven companies (excluding internships)

Proficiency in backend technologies. Our tech stack includes Python, FastAPI, and Postgres

Experience designing and scaling distributed systems, APIs, or data processing pipelines

Have experience building AI agents or applications, including designing evals and improving performance through prompting or scaffolding

Are familiar with evaluation methods for LLMs and have worked with patterns like multi-agent workflows, tool use, or long context.

Experience creating production evals and/or measuring performance of ML/LLM models at scale

Preferred

No preferred qualifications listed.