Risk Management Graduate Intern in San Francisco

About the Team The GTM Data Science team partners with Go-to-Market, Technical Success, Product, Engineering, RevOps, and Strategic Finance to build the shared intelligence layer for OpenAI's B2B business. The team turns product usage, customer behavior, revenue, field activity, and customer feedback into rigorous insight products that help leaders and field teams understand where customers are succeeding, where adoption is blocked, and what actions will accelerate durable growth. We are building systems that make customer intelligence proactive: surfacing risk, expansion potential, product gaps, and repeatable playbooks before they show up as escalations or missed opportunities. About the Role As the Applied Data Science & Insights Lead for GTM Intelligence Solutions and Technical Success, you will be a hands-on technical leader responsible for shaping how OpenAI measures, understands, and improves customer adoption across our B2B products. You will build AI/ML-powered intelligence products that connect account health, product usage, customer lifecycle, support tier, qualitative sentiment, commercial context, and field actions into a practical operating system for GTM and Technical Success. This role will build the data science foundation for Technical Success: defining the metrics, models, operating insights, and decision systems that help the team scale customer adoption and expansion with rigor. You will also be expected to build and lead a small mighty team over time: setting direction, hiring and developing talent, creating operating cadences, and holding a high bar for technical rigor and business impact. You will lead the development of models, metrics, and decision systems that recommend what GTM and Technical Success teams should do next, explain why, and measure whether those interventions worked. Your work will help customers move from pilots to production, deepen usage across products, identify high-value use cases, reduce churn risk, and create a f

About The Team OpenAI Finance is responsible for ensuring the organization is set up for success in pursuit of its mission. The Technical Accounting team plays a crucial role in helping OpenAI navigate complex, judgmental, and rapidly evolving accounting matters with rigor and clarity. We aim to bring both technical excellence and strong business partnership to some of the most novel accounting questions in the industry. About The Role OpenAI seeks a Director, Technical Accounting, Revenue & Strategic Partnerships to set the technical revenue accounting strategy for the company's largest, most complex, and highest-risk commercial arrangements. This leader will personally assess novel fact patterns, establish and defend the accounting position, and shape deal structures before execution across enterprise contracts, strategic partnerships, API and consumption-based offerings, credits and incentives, revenue share, multi-party arrangements, and emerging product monetization models. This role will be the senior technical accounting partner to Revenue Accounting, Sales, Product, Legal, Tax, Strategic Finance, Business Development, Deal Desk, Billing, Financial Reporting, Internal Controls, and external auditors. The core mandate is technical judgment: independently synthesize the full contractual and economic substance, identify alternatives and second-order implications, resolve ambiguity under ASC 606 and related U.S. GAAP, and communicate a clear recommendation to executives and auditors. Operational know-how is essential to translate conclusions into billing, close, disclosures, systems, and controls, but process ownership is not the center of the role. In This Role, You Will Partner closely with Revenue Accounting, Sales, Product, Legal, Tax, Strategic Finance, Business Development, Deal Desk, Billing, Financial Reporting, and external auditors. Identify non-standard revenue arrangements early and evaluate them under ASC 606. Advise on thoughtful deal structurin

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Threat Intelligence team protects OpenAI’s technology, people, research, and infrastructure by proactively identifying and disrupting adversaries who seek to compromise our systems or misuse our models. We investigate sophisticated threats, build tooling to scale and augment analysis, and deliver intelligence that shapes security strategy and equips leadership with timely, risk-aware insights. We combine technical depth, investigative rigor, and strong cross-functional partnerships to uncover threats and drive impact across OpenAI’s security and research organizations. About the Role As a Technical Threat Investigator at OpenAI, you will help protect the company from sophisticated adversaries targeting OpenAI and the broader ecosystem, as well as those attempting to misuse our models in support of cyber operations. This is a deeply investigative role. You will independently conduct complex, end-to-end investigations into capable threat actors to understand their behavior, infrastructure, emerging techniques, and how AI is integrated into their workflows. You’ll use these insights to proactively identify malicious activity and drive detection, disruption, enforcement, and safety improvements across the company. You’ll translate your investigative findings into durable solutions that scale impact. You’ll build and own lightweight tooling, automate where it matters, and create AI-assisted workflows to make investigations faster, more repeatable, and more effective over time. In this role, you will: Conduct deep, end-to-end investigations into sophisticated threat actors interacting with OpenAI’s models, products, and broader ecosystem. Think like an adversary — model attacker behavior, anticipate misuse patterns, and proactively hunt for, identify, and disrupt malicious activity. Leverage internal telemetry, OSINT, vendor data, a

About the Team Safety Systems works to ensure OpenAI’s most capable models can be developed and deployed responsibly. Our work spans evaluations, safeguards, red teaming, deployment decisions, and the systems that help OpenAI understand and reduce risk as models become more capable and widely used. Within Safety Systems, the Trustworthy AI team is growing its safety transparency function: a practice focused on helping external audiences understand OpenAI’s technical safety work with greater clarity, rigor, and continuity. We create and improve the public artifacts that explain how our systems are evaluated for safety, what safeguards we build, what decisions we make, and where uncertainty remains. This work includes system cards, the Deployment Safety Hub, safety-related blogs, public governance documents, and other outputs that communicate technical safety topics to external audiences. It also includes building new ways to make technical safety information easier to understand, navigate, and use—including AI-assisted workflows, data visualizations, and interactive tools that make complex technical work more legible over time. About the Role We are looking for a Safety Transparency Editor to own the editorial quality of key safety transparency artifacts and systems. This is a hands-on role for someone who can write crystal-clear, pitch-perfect explanations of the hardest and highest-stakes technical safety topics that OpenAI tackles, and who can lean into AI to build systems that help the broader organization do this work better. Your core responsibility is to shape and execute how our technical safety work is externally communicated: identifying the narrative thread, exercising judgment about which details matter, determining where additional context, explanation, or supporting evidence is needed, translating complexity without sacrificing precision, and helping external audiences understand both the safety measures we’ve taken and the uncertainties that remain. To

About the Team OpenAI’s Financial Engineering (FinEng) team powers how revenue flows through our products—pricing & packaging, checkout, payments, subscriptions, and the financial infrastructure behind them. We partner with Product, Engineering, Risk, Finance, and Go-to-Market to make paying for OpenAI products seamless, reliable, and efficient worldwide. About the Role As a Data Scientist on FinEng, you’ll own the analytics and experimentation that improve our checkout and payments , subscriptions , and pricing & monetization systems. You’ll define the metrics that matter, build the source-of-truth data assets, and design experiments that increase conversion, reduce churn and payment failures, and expand global payment method coverage. Your work will directly influence revenue, customer experience, and how we scale internationally. 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 will Own checkout & payments analytics and experimentation across methods and locales (e.g., bank transfers, emerging rails), improving conversion while monitoring risk and latency. Build and run the experimentation program for in-house checkout—define success metrics and guardrails, execute staged rollouts, and use offline incrementality when online tests aren’t feasible. Create operational visibility and source-of-truth data with FinEng Data Engineering—land team-level metrics, SLAs, and self-serve dashboards that drive proactive action. Lead subscription, retention, and monetization analytics—ship launch-readiness for new subscription features, reduce involuntary churn (e.g., targeted retrials/nudges), and develop elasticity/FX frameworks toward pricing optimality. You might thrive in this role if you have 5+ years in a quantitative role (data science, product analytics, or experimentation) in high-growth or fintech environments Fluency in SQL and Python ,

About the Team We are building general-purpose robotics. In the short term, we are focused on robots to support skilled workers to build our future infrastructure. In the long term, we imagine everyone having a personal robot doing anything they need. Progress is rapid, and based on a foundation of co-design between robotics hardware and ML research. About the Role As a Firmware Engineer, you will define and drive the architecture of embedded systems for next-generation hardware products. You will own foundational firmware decisions across real-time execution, device bring-up, hardware interfaces, fault handling, safety mechanisms, and production readiness. We’re looking for someone with deep experience building safety-critical or high-consequence systems, where failures can have meaningful consequences. You should be comfortable reasoning about risk, designing for diagnosability and graceful degradation, and creating engineering practices that raise the reliability bar for the entire team. You should also be unusually good at moving fast. Sometimes the right answer is a carefully reviewed architecture that will endure for years; sometimes it is getting a rough-but-useful prototype working by the end of the afternoon so the team can learn something concrete tomorrow. We value engineers who know the difference, make that call well, and can operate credibly in both modes. You will be both a technical leader and a hands-on builder: setting direction, reviewing critical designs, unblocking the hardest problems, and writing production firmware when it matters most. Our embedded stack uses a lot of Rust. Extensive experience in the language is a big help! This role is based in San Francisco, CA. This role will be expected to be in office 4 days per week and offer relocation assistance to new employees. In this role, you will: Rapidly bring up new hardware and set execution pace for the team. Lead firmware architecture for embedded systems spanning boot, RTOS/runtime behav

About the Team The Safety Systems team is dedicated to ensuring the safety, robustness, and reliability of AI models and their deployment in the real world. Learn more about OpenAI’s approach to safety. Building on the many years of our practical alignment work and applied safety efforts, Safety Systems addresses emerging safety issues and develops new fundamental solutions to enable the safe deployment of our most advanced models and future AGI, to make AI that is beneficial and trustworthy. About the Role At OpenAI, we're dedicated to advancing artificial intelligence, and we know that creating a secure and reliable platform is vital to our mission. That's why we're seeking a software engineer to help us build out our trust and safety capabilities. In this role, you'll work with our entire engineering team to design and implement systems that detect and prevent abuse, promote user safety, and reduce risk across our platform. You'll be at the forefront of our efforts to ensure that the immense potential of AI is harnessed in a responsible and sustainable manner. Your Responsibilities: Architect, build, and maintain anti-abuse and content moderation infrastructure designed to protect us and end users from unwanted behavior. Work closely with our other engineers and researchers to utilize both industry standard and novel AI techniques to measure, monitor and improve AI models’ alignment to human values. . Diagnose and remediate active incidents on the platform and build new tooling and infrastructure that address the root causes of system failure. You might thrive in this role if: You have built and run production services in a high growth, rapidly scaling environment. You can debug live issues and restore systems quickly. You have worked on content safety, fraud, or abuse, or are motivated and excited to work on present-day (“now-term”) AI safety. You have experience with Python or with modern languages such as C++, Rust, or Go, and are able to quickly ramp up on Py

About the role We’re looking for an engineering manager to lead a team building software systems that detect and prevent harmful misuse of frontier AI models—before incidents occur. This is a builder’s role: you’ll lead engineers shipping production services, detection pipelines, and mitigation mechanisms that protect frontier model integrity and reduce high-severity misuse risk. While this work intersects with frontier model development, security and risk, we’re explicitly seeking someone with a software engineering foundation who is comfortable building reliable systems that can operate at billions of users scale. In this role you will: Lead a team of software engineers building detection + mitigation systems for frontier model misuse, with an emphasis on model IP protection / distillation detection and emerging risk surfaces from autonomous agents. Set the technical roadmap and execution strategy: prioritize, design, ship, iterate, measure impact. Build production systems: services, pipelines, tooling, instrumentation, and automation that scale with frontier model usage. Partner deeply with Research and Product to translate evolving model capabilities into concrete tests, signals, and mitigations that can be deployed at scale. Drive strong engineering fundamentals: architecture, reliability, monitoring, performance, and operational excellence. Hire and grow an exceptional team across backend, data systems, and applied ML engineering domains as needed. Anticipate what breaks at scale as agentic workflows become more capable. You might thrive in this role if you: Experience building systems in adversarial, fast-evolving environments Are comfortable with ambiguity and novelty Have experience adjacent to security (e.g., abuse prevention, fraud, integrity, platform defense, auth/identity, malware/spam, adversarial environments) Communicate clearly and build trust quickly with senior stakeholders—pragmatic, collaborative, and calm under scrutiny. Significant experience

About the Role We’re looking for a senior Strategic Finance Lead to help shape and execute OpenAI’s financial strategy across some of the company’s most important long-term investments and growth priorities. This high-impact role sits at the intersection of corporate finance, capital markets, treasury, and cross-functional execution. In this role, you will: Shape financial strategy for major long-term investments, capital structure decisions, and broader strategic decision-making. Build rigorous financial models and scalable frameworks to evaluate strategic initiatives, funding options, tradeoffs, and risk. Structure and help execute complex strategic initiatives in partnership with cross-functional teams. Translate ambiguous technical and business inputs into clear recommendations and decision-ready materials for executives, the board, and other senior stakeholders. Lead high-priority cross-functional workstreams from concept through execution, bringing strong judgment, ownership, and communication in fast-moving situations. Help build an AI-native finance organization by applying AI to improve workflows, decision-making, and execution across finance processes. You might thrive in this role if you have: 12+ years of experience across strategic finance, corporate finance, capital markets, investment banking, infrastructure finance, or related fields. A strong understanding of capital structure, financing strategy, debt markets, and large-scale investment evaluation. Experience operating in high-growth, high-complexity environments with the ability to navigate ambiguity and move quickly. Exceptional financial modeling, strategic thinking, and problem-solving capabilities. Strong executive presence with the ability to communicate clearly across investors, executives, and technical stakeholders. A high-agency operating style that combines strategic perspective with a willingness to build directly. Excitement around using AI as a core operating advantage, with a mindset

About the Role The Engineering Acceleration Delivery / Continuous Deployment team builds and operates the systems that safely ship OpenAI’s infrastructure and product code to production. We own the deployment platform, release pipelines, and rollout safety mechanisms that allow engineers across OpenAI to deploy changes rapidly while minimizing operational risk. Our mission is to make production deployments fast, safe, and increasingly autonomous. This role sits at the intersection of developer productivity, distributed systems reliability, and large-scale infrastructure orchestration. In This Role, You Will Design and build continuous deployment infrastructure that safely rolls out changes across dozens of Kubernetes clusters and global regions. Develop systems for progressive delivery, including canary releases, staged rollouts, and automated rollback. Improve engineering velocity by reducing friction in the release pipeline and automating manual operational workflows. Work with product and infrastructure teams to ensure their services are deployable, observable, and resilient at scale. Implement and evolve deployment methodologies such as GitOps, infrastructure-as-code, and progressive delivery patterns. Build systems that automatically evaluate deployment health using metrics, logs, traces, and alerts to detect regressions and trigger safe rollbacks. Build systems that support agent-assisted or autonomous deployment workflows using modern AI tooling. Technologies commonly used in this environment include: Kubernetes for large-scale container orchestration and runtime infrastructure Python and FastAPI for internal services Terraform for infrastructure as code GitOps-based deployment workflows (e.g., ArgoCD, Flux, or similar systems) Buildkite for CI orchestration You may be a strong fit if you: Have worked with Kubernetes-based deployment systems at scale Have experience building or operating continuous deployment platforms Are familiar with GitOps tooling such as

About the Team Consumer Monetization builds the experiences and systems that power how customers purchase and pay for OpenAI products. Our scope spans purchasing flows, payments, subscriptions, and billing, along with the shared capabilities that support new products, offers, and distribution channels. We own both customer-facing experiences and the underlying platforms that power them. We partner closely with Product, Design, Growth, Data Science, and engineering teams across OpenAI to make purchasing effective and reliable, and new offerings easier to launch and monetize. About the Role We’re looking for experienced Staff+ engineers to evolve the payments, billing, and subscription capabilities that support OpenAI’s growing product portfolio. You’ll tackle problems where correctness, reliability, and flexibility are essential: supporting new billing requirements, managing the billing lifecycle, synchronizing state across internal systems and external providers, and enabling new products and commercial models. Your work may span several areas based on your expertise and team priorities: Billing and monetization capabilities: Extend billing capabilities and improve integrations and state consistency across systems to support new products and business models. Subscriptions: Orchestrate purchases, renewals, plan changes, cancellations, and recovery, ensuring customers are charged correctly and receive the right benefits. Payments: Expand payment capabilities through processor integrations, routing, and broader payment-method coverage. Risk and integrity: Partner with risk and integrity teams to integrate controls into purchasing flows, reducing abuse while protecting legitimate customer experiences. You’ll help set technical direction while remaining hands-on in implementation and delivery. This is an opportunity to solve complex engineering problems at scale, connect architecture decisions to customer and business outcomes, and help other engineers take on broader ow

About the Team OpenAI Finance helps ensure the organization is set up for success in pursuit of its mission of ensuring that artificial general intelligence benefits all of humanity. Within Finance, the Technical Revenue team partners with Product, Legal, GTM, Strategic Finance, Revenue Accounting, Finance Systems, and the company’s GTM Deal Desk organization to enable scalable, audit-ready monetization. We advise on commercial and contract design, establish defensible accounting positions under ASC 606, and provide clear conclusions and handoffs for downstream execution by Revenue Accounting Operations. About the Role We’re looking for a Senior Manager of Technical Revenue Enablement to lead Revenue Recognition deal advisory for OpenAI’s general B2B commercial activity. Reporting to the Head of Technical Revenue, you will serve as the primary Revenue Recognition counterpart to OpenAI’s Deal Desk organization, partnering with Legal, GTM, Product, Pricing, and Strategic Finance throughout the presignature deal lifecycle. You will own intake and triage, advise on non-standard terms, approve arrangements supported by established policy and precedent, and route novel or strategic matters to the appropriate technical owner. You will build a scalable deal-advisory model by translating ASC 606 into practical contract guardrails, approved language, decision trees, review thresholds, and clear service levels. This role requires deep technical accounting judgment, commercial fluency, strong stakeholder influence, and the ability to make timely, risk-based decisions in a fast-moving environment. 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 will: Lead the Revenue Recognition deal-advisory function for general B2B transactions, serving as the primary finance counterpart to OpenAI’s GTM Deal Desk organization. Partner early with GTM Deal Desk, Legal, GTM, Pr

About the Team OpenAI Finance helps ensure the organization is set up for success in pursuit of its mission of ensuring that artificial general intelligence benefits all of humanity. Within Finance, the Revenue Accounting, Technical team partners with Product, Strategic Partnerships, Business Development, Growth, Legal, Deal Desk, GTM, Strategic Finance, Revenue Accounting, and Finance Systems to enable scalable, operationally sound monetization. We advise on commercial and contract design, establish clear accounting positions under ASC 606, and translate those conclusions into repeatable processes, systems, controls, and reporting. About the Role We’re looking for a Manager of Revenue Accounting, Technical to drive the end-to-end technical revenue and operational workstream for OpenAI’s strategic commercial deals—from early structuring and deal-desk review through contracting, launch, and ongoing governance. Reporting to the Head of Revenue Accounting, Technical, you will serve as a key revenue advisor for complex and non-standard strategic deals, translating commercial objectives into revenue models that are economically sound, accounting-compliant, and operationally executable. You will partner with senior team members on the most novel or high-risk matters across strategic collaborations, cloud marketplaces, platform and distribution deals, licensing and revenue-share models, joint go-to-market initiatives, research collaborations, and other emerging commercial structures. You will engage from the earliest stages of a deal to shape economics, pricing, commercial terms, contract language, and product design; define the supporting data, billing, settlement, reporting, systems, controls, and revenue-recognition model; and drive cross-functional readiness through launch. After launch, you will help govern amendments, monitor whether the model is operating as intended, resolve execution issues, and evolve the approach as the partnership or business model changes. Thi

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. Plaid’s Partnerships team develops strategic relationships with technology platforms and other ecosystem partners that expand the reach and impact of Plaid’s products. This role will focus on data and product partnerships that power Plaid’s Credit products and insights. Plaid’s Credit team is building the future of lending by making cash flow data as widely used and trusted as traditional credit data. Our mission is to expand access to more affordable credit by giving lenders real-time financial insights that improve risk assessment and decision-making at scale. In this role, you will build and manage the external data partnerships that power Plaid’s Credit products. The partner ecosystem is broad and includes traditional credit data providers, alternative data providers, financial infrastructure companies, and other sources of differentiated data and insights. You will work closely with Product and Engineering to understand where new data can improve existing products or unlock entirely new capabilities. You will identify and prioritize partners, develop creative commercial structures, and negotiate complex agreements that balance product, economic, and strategic considerations.

About the Team Safety Systems manages the complete lifecycle of safety efforts for OpenAI’s frontier models, ensuring our models are deployed responsibly and have a positive impact on society. Our work spans diverse research and engineering initiatives—from system-level safeguards and model training to evaluation and red-teaming—all aimed at mitigating misuse, misalignment, and maintaining our high bar for safety. We lead OpenAI's commitment to developing and deploying safe Artificial General Intelligence (AGI), fostering a culture of trust, responsibility, and transparency. Our goal is to continuously learn from deployments, distribute AI’s benefits widely, and ensure that powerful tools remain aligned with human values and safety considerations. Within Safety Systems, the Model Policy team works to ensure that frontier models behave safely and reliably in real-world environments by designing policies that define safe model behavior. Some of our publications include: Safety at every step OpenAI GPT6 System Card OpenAI Model Spec About the Role We’re hiring a Model Policy Manager to shape model behavior for U.S. government use, with a focus on national security applications. You’ll define nuanced policies and translate them into training and evaluation criteria, helping models navigate high-stakes scenarios while preserving their usefulness and capabilities. In this role, you will: Develop model policies that guide safe and useful behavior. Build evaluations, identify policy gaps and model failures, and use findings to improve policies and training. Work with research, engineering, and domain experts to support safe, reliable deployment. You might thrive in this role if you: Bring relevant experience in AI safety, policy, or risk assessment. Have strong judgment and can turn complex safety questions into clear, practical policies. Have the technical fluency to work hands-on with model data and evaluations. Are motivated by OpenAI’s mission and the responsible use of