Why This Job is Featured on The SaaS Jobs
This role stands out in the SaaS landscape because it sits at the boundary between productized AI and platform governance. For AI companies that deliver models through APIs and enterprise products, policy is not an external compliance layer but an operational input to how the service behaves in production. The focus on chemical and biological risk highlights a maturing segment of the ecosystem where safety constraints increasingly shape what can be shipped, monitored, and supported.
From a SaaS career perspective, the work builds durable expertise in translating ambiguous risk domains into repeatable frameworks that can be implemented across the model lifecycle. That includes creating taxonomies that drive data collection and evaluation, and defining criteria that can be used to assess releases over time. Experience in making policy actionable for training and deployment tends to transfer across AI SaaS contexts where reliability, auditability, and incident response are core to customer trust.
The role is best suited to senior operators who enjoy classification problems, structured writing, and decision-making under uncertainty. It will fit professionals who prefer cross-functional influence over narrow ownership, and who are motivated by connecting research realities to enforceable standards that can be applied at scale.
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 Safety Systems team is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency.
The Model Policy team aligns model behavior with desired human values and norms. We co-design policy with models and for models by driving rapid policy taxonomy iteration based on data and defining evaluation criteria for foundational models’ ability to reason about safety. Key focus areas include: catastrophic risk, mental health, teen safety and multimodal safety.
About the Role
Providing access to powerful AI models introduces a host of challenging questions when it comes to model safety: How do we define safe behavior for how a model should behave? To what end? How do we do this in such a way that is actionable, objective and sustains replicability?
This is a senior role in which you’ll help shape policy creation and development at OpenAI and make an impact by helping ensure that our groundbreaking technologies do not create harm. The ideal candidate can identify and develop cohesive and thoughtful taxonomies of harm on high risk topics with a sense of urgency. They can balance internal and external input in making complex decisions, carefully think through trade-offs, and write principled, enforceable policies based on our values. Importantly, this role is embedded in our research teams and directly informs model training.
This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.
In this role, you’ll:
Design model policies that govern safe model behavior in an objective and defensible way - e.g. how should the model respond in risky/unsafe scenarios? What does unsafe mean? How do we achieve safety while preserving beneficial model capabilities?
You will develop taxonomies that inform data collection campaigns, model behaviour and monitoring strategies and also toe the line between maximizing utility and preventing catastrophic risk.
Lead prioritization for safety efforts across the company for new model launches, understanding and addressing technical and business trade-offs.
Develop a broad range of subject matter expertise while maintaining agility across topics.
You will work across many internal teams which will require high organizational acumen and confident decision making.
You might thrive in this role if you:
Have extensive experience researching LLMs, ML, AI, tech policy, moral reasoning, and/or enjoy classification problems.
Have extensive experience defining, refining and enforcing policies for ML models across training, evaluation, and deployment.
Understand the practical challenges of translating policy into model behavior across the full training stack, and can incorporate these constraints into policy design.
Can reason about the benefits and risks of open-ended problem spaces, generate novel approaches under ambiguity, and take full ownership of end-to-end solutions from concept through execution.
Most relevant publications:
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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