Why This Job is Featured on The SaaS Jobs
This backend engineering role stands out in the SaaS ecosystem because it focuses on the operational backbone of AI-enabled support, a domain where product quality is inseparable from measurement. Rather than building customer-facing features, the work centers on evaluation infrastructure that determines whether automation is reliable over time, which is increasingly core to SaaS companies adopting LLMs in service workflows.
For a long-term SaaS career, the emphasis on reproducible pipelines, continuous monitoring, and feedback loops builds durable skills in platform thinking. Experience designing APIs and services that integrate data across internal systems maps directly to how modern SaaS organizations scale operations: by turning messy operational signals into dependable inputs for downstream tools. The cross-functional partnership with data science and research also reflects a growing pattern in SaaS engineering, where model behavior and system behavior must be managed together.
This role is best suited to an engineer who prefers ownership of foundational systems and is comfortable balancing iteration with maintainability. It fits someone who enjoys rigorous measurement, production reliability, and the practical constraints of deploying ML-adjacent systems inside a real organization, particularly in an on-site environment with close collaboration.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
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
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
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