As the portfolio grows, this role is expected to evolve into team leadership. You'll play a key role in shaping how risk decisions translate into customer experience, product growth, and long-term portfolio performance.

Key responsibilities include:

• Building and operationalizing the credit strategy

• Translating underwriting vision into formal credit policy and decision frameworks

• Defining approval logic, segmentation strategy, and limit-setting methodology

• Establishing portfolio guardrails aligned to loss targets and unit economics

• Designing account management strategies across the customer lifecycle

• Developing early portfolio management approaches including exposure adjustments, servicing strategies, and input into collections processes as the portfolio matures

• Defining portfolio monitoring frameworks and escalation triggers for emerging credit risk trends

• Building the data-driven risk engine

• Implementing credit policy in our underwriting platform

• Evaluating and integrating key data sources (bureau, income, debt signals)

• Ensuring decision logic is structured, testable, and scalable

• Partnering with Engineering and Data to build monitoring and feedback loops

• Owning portfolio performance post-launch

• Defining and tracking core KPIs (approval rate, early delinquency, loss rate, exposure, utilization, etc.)

• Monitoring vintage performance and segment behavior

• Recommending and implementing strategy adjustments based on observed risk trends

• Presenting risk performance, insights, and recommendations to senior leadership

• Driving data-informed risk and growth decisions

• Using SQL to independently evaluate underwriting decisions and trade-offs

• Analyzing drivers of credit performance and portfolio outcomes

• Partnering with Finance on forecasting and risk-adjusted economics

• Driving cross-functional execution

• Partnering with Compliance to ensure the underwriting program is well-documented and built to scale

• Working with Partnerships, Procurement, and Legal on evaluating and onboarding credit data providers

• Supporting broader risk initiatives across our business charge card portfolio during the build phase

Requirements include:

• 6+ years of experience in consumer credit risk
• Experience launching or materially redesigning a consumer lending product
• Experience implementing credit policy within a decisioning or underwriting platform is strongly preferred
• Demonstrated experience owning risk strategy and monitoring portfolio performance
• Deep familiarity with bureau data and core credit risk metrics (approval rate, loss rate, vintage curves, etc.)
• Experience presenting risk insights and strategy recommendations to senior stakeholders
• Experience translating policy into production decision logic
• Strong SQL skills and comfort working directly with data
• Comfortable building in ambiguity and operating in a 0→1 environment

Total rewards package includes base salary, equity, and benefits. Salary and equity ranges are highly competitive within the SaaS and fintech industry.

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San Francisco

Employment Type

Full time

Department

Applied AI

Compensation

• $230K – $385K • 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 Monetization team is a new cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products—including next-generation ads experiences—that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation.

Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers and businesses.

This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring research breakthroughs into real-world systems at global scale.

About the Role

We’re looking for experienced Software Engineers to help build OpenAI’s foundational ads ranking and recommendation systems—the ML and AI platforms that determine how monetized experiences are selected, ordered, and optimized across OpenAI products.

In this role, you’ll architect and implement large-scale, high-performance ML-driven systems with rigorous requirements around latency, correctness, safety, privacy, and continuous improvement. You’ll work on modern, transformer- and LLM-inspired architectures that move beyond traditional feature engineering toward more expressive, context-aware decisioning. Your work will have a direct revenue impact and make ChatGPT and other products accessible to more people with fewer usage limits or without having to pay.

This is a deeply technical, 0→1 founding-stage role where you’ll operate across backend engineering, systems design, and applied AI/ML to help define the next generation of AI-native monetization and recommendation platforms.

This role is exclusively based across our San Francisco and Seattle sites. We offer relocation assistance to new employees.

In this role, you will:

• Architect, build, and evolve large-scale ads ranking and recommendation systems using modern ML and AI techniques

• Design and productionize LLM- and transformer-inspired models that leverage sequential signals, long-horizon context, and sparse or delayed feedback.

• Develop model-driven decision logic and inference pipelines that operate under real-world constraints around performance, reliability, and privacy.

• Partner closely with Product, Design, and Research to define requirements and translate ambiguous product goals into scalable ML systems.

• Prototype, experiment, and rapidly iterate on new model architectures and training approaches to improve relevance, quality, and efficiency.

• Build services and infrastructure that support training, evaluation, online inference, and continuous optimization of ML models.

• Establish strong measurement, experimentation, and debugging practices to understand model behavior and system-level outcomes.

• Contribute to technical strategy and help shape the long-term evolution of OpenAI’s monetization and recommendation stack.

• Embed safety, fairness, and policy considerations directly into model design and system architecture from first principles.

You might thrive in this role if you:

• Have 6+ years of experience building and scaling ML-powered systems in production environments.

• Have worked on ranking, recommendation, ads, marketplaces, or large-scale ML inference systems.

• Are comfortable operating across the full stack — from model development to backend services and production deployment.

• Enjoy deeply technical 0→1 problem spaces where architecture, strategy, and implementation overlap.

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