This role sits within the Integrity & Authenticity (I&A) team, where you will function both as a policy owner and work closely with threat investigative and enforcement teams.

Key responsibilities include drafting, maintaining, and iterating on Fraud & Scams policies; conducting regular structured policy reviews; developing detailed threat models for fraud and scam vectors; and staying current on the fraud and scam landscape.

You will also design and architect automated enforcement systems and human review workflows that scale effectively while maintaining high precision and recall.

Additionally, you will serve as the primary policy point of contact for ML and Engineering teams developing fraud detection classifiers, working to translate policy intent into technical artifacts and training signals.

If you have experience working as a Trust & Safety professional with a focused background in fraud, scams, or financial crime, particularly in a tech platform or AI context, you may be a good fit for this role.

Preferred qualifications include experience at a major technology platform, financial institution, or fraud intelligence firm in a policy, operations, or investigative capacity, familiarity with the generative AI risk landscape, and background in threat intelligence, financial crimes compliance (AML/KYC), or law enforcement focused on cyber-enabled fraud.

The annual compensation range for this role is $245,000-$285,000 USD.

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This role sits within the Integrity & Authenticity (I&A) team, where you will function both as a policy owner and work closely with threat investigative and enforcement teams.

Key responsibilities include drafting, maintaining, and iterating on Fraud & Scams policies; conducting regular structured policy reviews; developing detailed threat models for fraud and scam vectors; and staying current on the fraud and scam landscape.

You will also design and architect automated enforcement systems and human review workflows that scale effectively while maintaining high precision and recall.

Additionally, you will serve as the primary policy point of contact for ML and Engineering teams developing fraud detection classifiers, working to translate policy intent into technical artifacts and training signals.

You may be a good fit if you have experience working as a Trust & Safety professional with a focused background in fraud, scams, or financial crime, particularly in a tech platform or AI context.

Preferred qualifications include experience at a major technology platform, financial institution, or fraud intelligence firm in a policy, operations, or investigative capacity, familiarity with the generative AI risk landscape, and background in threat intelligence, financial crimes compliance (AML/KYC), or law enforcement focused on cyber-enabled fraud.

The annual compensation range for this role is $245,000-$285,000 USD.

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We are seeking an IT Administrator - Endpoint Management to own the enterprise endpoint strategy with primary responsibility for administering Replit’s MDM platforms, enforcing secure baseline configurations aligned to CIS Level 1 benchmarks and ensuring all corporate endpoints (primarily macOS) are properly patched, compliant, and securely configured.

What You'll Do

• Own and administer enterprise endpoint management platforms with primary responsibility for Iru/Kandji configuration, policy design, and lifecycle management

• Establish and enforce enterprise endpoint standards aligned to CIS Level 1 benchmarks

• Design, implement, and maintain secure baseline configurations for macOS endpoints ensuring systems are hardened and secure by default

• Ensure all endpoints remain compliant with patching policies, minimum OS requirements, and approved software versions through automated enforcement

• Administer and maintain an internal approved application catalog including packaging, version control, testing and secure deployment

• Ensure endpoint detection and response (EDR) tooling is properly deployed, configured and monitored (SentinalOne preferred)

• Implement and enforce appropriate data loss prevention (DLP) measures across endpoints to protect corporate data and intellectual property

• Develop compliance dashboards and reporting to track endpoint posture, remediation timelines and risk exposure

• Partner closely with Security Operations (SecOps) to investigate, contain, and remediate endpoint-related security incidents

• Participate in incident response activities including forensic coordination, containment actions and post-incident remediation

• Contribute to internal and external audits, ensuring endpoint controls meet SOC 2 and ISO 27001 requirements; prepare evidence and support auditor walkthroughs

• Own licensing strategy across administered platforms, ensuring appropriate license assignment, cost optimization, feature alignment, renewal management and utilization reporting

• Continuously evaluate new endpoint features, security capabilities, and OS updates

• Create and maintain technical documentation, configuration standards and operational runbooks

Required Skills & Experience

• 6+ years of experience in endpoint administration, device management, and enterprise IT operations in a cloud-first environment

• Hands-on expertise administering Iru/Kandji or comparable Apple-focused MDM solutions

• Understanding of MDM solutions for Microsoft Windows and Linux (Jump Cloud preferred)

• Strong understanding of CIS Level 1 controls and endpoint hardening principles

• Experience deploying and administering EDR solutions and coordinating with security teams on alert triage and remediation

• Experience managing OS patching strategies, update enforcement policies and compliance reporting

• Familiarity with DLP technologies and endpoint-based data protection controls

• Experience participating in compliance programs aligned to SOC 2 and ISO 27001 frameworks supporting audit evidence collection and control validation processes

• Strong troubleshooting skills with the ability to diagnose complex endpoint configuration and policy conflicts

• Clear documentation and communication skills with the ability to articulate technical risk and remediation strategies

Bonus Qualifications

• Active Replit user and passionate about making software creation more accessible

• Been part of a rapid growth SaaS startup

Full-Time Employee Benefits Include

• Competitive Salary & Equity

• 401(k) Program with a 4% match

• Health, Dental, Vision and Life Insurance

• Short Term and Long Term Disability

• Paid Parental, Medical, Caregiver Leave

• Commuter Benefits

• Monthly Wellness Stipend

• Autonomous Work Environment

• In Office Set-Up Reimbursement

• Flexible Time Off (FTO) + Holidays

• Quarterly Team Gatherings

• In Office Amenities

Want to learn more about what we are up to?

• Meet the Replit Agent

• Replit: Make an app for that

• Replit Blog

• Amjad TED Talk

Interviewing + Culture at Replit

• Operating Principles

• Reasons not to work at Replit

Compensation Range

$95K - $175K

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Model Policy Manager, Youth Well-being

Location

San Francisco

Employment Type

Full time

Department

Safety Systems

Compensation

• Estimated Base Salary $207K – $295K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

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:

• Introducing HealthBench

• Preparing for future AI capabilities in biology

• Safety evaluations hub

• OpenAI GPT5 System Card

• Evaluating Fairness in ChatGPT

• Improving Model Safety Behavior with Rule-Based Rewards

• OpenAI Model Spec

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 of individuals from all walks of life.

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San Francisco

Employment Type

Full time

Department

Safety Systems

Compensation

• Estimated Base Salary $207K – $295K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

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 frontier AI systems raises complex questions around dual-use science and catastrophic risk. How should models respond to requests involving chemical synthesis, biological experimentation, or pathogen research? Where is the boundary between legitimate scientific inquiry and information that could enable misuse? How do we design policies that meaningfully reduce risk without unnecessarily restricting beneficial research?

This is a senior role in which you’ll help shape policy creation and development at OpenAI for addressing biological and chemical risks. You will develop structured policy frameworks and taxonomies to guide safe model behavior. This role sits at the intersection of biosecurity expertise, AI safety research, and policy design. You will help ensure that frontier AI systems can support beneficial life sciences research, such as drug discovery, public health, and biosafety, while reducing the risk that these capabilities could be misused.

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 and maintain model policies governing chemical and biological risk, defining how models should safely handle dual-use scenarios.
• Develop structured taxonomies of chemical and biological risk that inform model training data, evaluation benchmarks, and safety monitoring systems.
• Translate biosecurity and chemical security expertise into actionable model behavior, working closely with research and engineering teams to operationalize policy in training and evaluation pipelines.
• Develop a broad range of subject matter expertise while maintaining agility across topics.
• Identify emerging risk vectors where frontier AI capabilities could meaningfully lower barriers to harmful activity and develop mitigation strategies.
• Engage with internal and external subject-matter experts in biosecurity, biodefense, and chemical safety to ensure policies reflect real-world risk landscapes.

You might thrive in this role if you:

• Have strong domain expertise in chemistry, biology, biosecurity, or related fields and are motivated to translate that expertise into principled, operational policies that scale to frontier AI systems.
• Have experience researching or working with LLMs, machine learning, AI governance, technology policy, or related areas, and enjoy tackling structured reasoning and classification problems—such as defining boundaries between legitimate scientific inquiry and potentially harmful applications.
• Have experience designing, refining, or enforcing policies or safeguards for complex systems, whether in AI/ML environments, scientific research governance, national security contexts, or other high-stakes technical domains.
• Are comfortable navigating ambiguous, high-stakes problem spaces, balancing risk reduction with the benefits of scientific openness and innovation.
• Enjoy building new frameworks from first principles, reasoning about open-ended problems, and generating novel approaches under uncertainty. You take ownership of problems end-to-end—from defining the conceptual framework through collaborating with research and engineering teams

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