Backend developer • daly city ca
The Support Automation team at OpenAI scales the organization by applying cutting-edge AI models to real-world challenges, automating and enhancing work across the organization.From customer operat...Show more
Senior Backend Engineer - Onsite - San Francisco, CA.Experience at well-known, top tech companies, either tier-1 VC-backed or FAANG, is mandatory.Experience with an OLAP or columnar database (e.Exp...Show more
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The average salary range is between $ 110,510 and $ 161,200 year , with the average salary hovering around $ 133,201 year .
The average salary range is between $ 106,502 and $ 156,769 year , with the average salary hovering around $ 125,000 year .
About the Team
The Support Automation team at OpenAI scales the organization by applying cutting-edge AI models to real-world challenges, automating and enhancing work across the organization. From customer operations to engineering, we develop an ecosystem of automation products that empower our colleagues and drive impact. We're passionate about crafting products that serve those around us, blending rapid prototyping with a focus on long-term quality and reliability. By creating reusable solutions, we create patterns that can be applied across diverse domains within OpenAI.
TLDR: this team leverages OpenAI technology to improve OpenAI, and you’ll have the opportunity to leverage the full extent of our tech (both public and pre-released) to accomplish this mission.
About the Role
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.
In this role, you will:
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
You might be a great fit if you have:
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
A pragmatic mindset. You’re comfortable shipping iteratively while building toward a long-term vision
