Incident Response Analyst in San Francisco

About the Team The Applied Foundations team at OpenAI is dedicated to ensuring that our cutting-edge technology is not only revolutionary but also secure from a myriad of adversarial threats. We strive to maintain the integrity of our platforms as they scale. The Applied Foundations team is at the front lines of defending against financial abuse, scaled attacks, and other forms of misuse that could undermine the user experience or harm our operational stability. Integrity Foundations provides the core building blocks and infrastructure for this work. About the Role At OpenAI, our mission is to advance AI in a way that is safe, reliable, and aligned with broad societal values. The applied foundations role is crucial for maintaining the trustworthiness of our platforms. You will be pivotal in developing robust defenses against a spectrum of adversarial behaviors that threaten our ecosystem. 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. In this role, you will: Develop and enhance systems to detect and prevent various forms of abuse including financial fraud, botting, and scripting. Collaborate with cross-functional teams to design solutions that protect against and mitigate adversarial attacks without compromising user experience. Assist with response to active incidents on the platform and build new tooling and infrastructure that address the fundamental problems. You might thrive in this role if you: Have at least 3 years of professional software engineering experience. Have experience setting up and maintaining production backend services and data pipelines. Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed. Are self-directed

About the Team OpenAI’s User Operations team shepherds our customers’ adoption of AI and ensures that our customers' product experience is nothing short of exceptional. We are building the very first post-AGI support team. We resolve complex issues, provide technical guidance, and support customers in maximizing value and adoption from deploying our products. We work closely with Sales, Technical Success, Product, Engineering and others, to deliver the best possible experience to our customers at scale. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. About the Role We are looking for a hands-on lead to build and run OpenAI's Incidents & Escalations function within User Operations. This is a player-coach role with a meaningful hands-on operating component. You will set the operating model and also step into active incidents and urgent escalations when needed, coordinating with on-call teams, driving clear ownership, supporting communications, and ensuring issues move through resolution and post-incident closure. During active incidents, you will coordinate with the relevant on-call teams and cross-functional responders across Engineering, Infrastructure, Support Delivery, Product, and Go-To-Market. You will help keep teams aligned, maintain timelines, clarify ownership, escalate when needed, and ensure internal, executive, customer-facing, and external communications are accurate and timely, including status page updates when required. For escalations, you will build and run the processes for tracking, triaging, mitigating, and resolving critical customer and user issues. After incidents and escalations, you will own the follow-through: retrospectives, root cause identification, action item tracking, trend analysis, and process improvements that reduce repeat issues over time. You will also help define the long-term operating model for incidents and escalations across Support D

About the Team OpenAI's Industrial Compute organization is building and operating the infrastructure foundation for the next generation of AI. Infrastructure Operations works across facilities, hardware, network operations, incident management, data center engineering, delivery teams, and external partners to bring capacity online safely, understand its operational state, and improve it over time. As OpenAI's data center portfolio grows across first-party and partner-delivered capacity, the organization needs clear goals, trusted data, repeatable processes, and systems that make ownership, risk, readiness, and performance visible. This role will help build the operating mechanisms that allow Infrastructure Operations to scale with rigor. About the Role We are seeking a Technical Program Manager to own the systems, data, reporting, governance, and program-management backbone for Infrastructure Operations. Reporting to the Delivery & Operations Lead, you will translate strategy into executable goals and operating cadences, turn operational needs into software and data solutions, and create the mechanisms that keep a rapidly evolving organization aligned and accountable. This role will also own the current 1P+3P delivery-tracking layer within Operations: milestones, delivery timelines, quantity forecasts, risks, decisions, and executive reporting. You will partner closely with 1P Delivery Program Management, Compute TPMs, Data Center Engineering, construction, commissioning, and operations leaders to ensure that delivery information becomes complete, usable input for readiness, handover, and ongoing operations. You will own program health and the operating system around it: the goals, data definitions, workflows, reporting, decision paths, and follow-through that help functional DRIs execute. The ideal candidate is comfortable in ambiguity, technically fluent enough to implement real systems, and relentless about converting scattered information into durable mechan

What you’ll do Design and implement secure cloud pipelines that ingest very large scan datasets (multi-terabyte), reliably and resumably. Build orchestration for GPU-accelerated reconstruction and analysis with strong retry semantics, idempotency, and cost controls. Define end-to-end data lifecycle for medical imaging: raw vs intermediate vs derived artifacts, retention policies, and reproducibility. Implement security + compliance primitives appropriate for HIPAA/PHI: encryption in transit/at rest, key management, least privilege, audit logs, and access reviews. Build operational tooling: monitoring, alerting, runbooks, and incident-driven improvements for a growing device fleet. What we’re looking for Strong experience with cloud batch/queueing/orchestration, storage systems, and data pipeline reliability. Experience shipping production systems that handle large data volumes and failure-prone networks. Practical security mindset (least privilege, secrets, audit logging) and comfort operating in compliance-constrained environments. Useful experience Building reliable data pipelines at scale (queues/orchestration, resumable uploads, GPU batch execution) with strong observability. Security + privacy by default: encryption, least-privilege access, auditing, and practical HIPAA/PHI guardrails. Owning the “boring” backend details that keep a lean team moving: schemas/migrations, cost controls, retries, and runbooks. Understanding compute tradeoffs across hardware options, and specifying appropriate cloud resources.

Why join us Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. Engineering at Brex Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level — from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders. What you’ll do As a Senior Software Engineer, Infrastructure (Release Engineering) at Brex, you will design, build, and operate the core systems that power Brex’s release, observability, and incident management processes. You will partner closely with product, platform, and operations teams to ensure releases are safe, fast, and reliable, and that our infrastructure scales securely as Brex grows. Where you’ll work This role will be based in our San Francisco office. We are a hybrid environment that combines the energy and connect

About the Team OpenAI’s Legal team helps advance our mission by tackling novel legal issues in AI. Our team brings together professionals across technology, privacy, intellectual property, corporate, employment, tax, regulatory, and litigation. Our regulatory compliance work turns legal requirements into practical programs that support responsible AI development and deployment. About the Role As a Legal Program Manager focused on regulatory compliance, you will build and manage cross-functional programs that translate counsel’s guidance into practical, sustainable operations. Your initial focus may include content moderation and/or frontier AI governance, with the mix shaped by team priorities and your strengths. You will partner with internal and external counsel, other legal program managers, and technical and business teams to coordinate implementation, evidence collection, reporting, and ongoing compliance. You’ll build repeatable systems that scale across regulations, products, and jurisdictions, helping teams navigate emerging requirements with clarity and sound judgment. This full-time role is based in San Francisco, CA, or New York, NY. In this role, you will: Lead regulatory compliance programs end to end: define scope, owners, milestones, dependencies, risks, and escalation paths, and drive execution with counsel and cross-functional partners. Translate counsel’s regulatory guidance into repeatable workflows, controls, and documentation. Depending on your portfolio, this may include content moderation disclosures, transparency reporting, reporting and appeals workflows, or frontier AI model launch readiness, evaluation and risk-management evidence, and incident reporting. Build strong partnerships across Product, Engineering, User Operations, Governance, Risk and Compliance (GRC), Global Affairs, Communications, and Go-to-Market to align program priorities and deliverables. Support regulatory inquiries, audits and investigations with counsel, organizing ev

About the Team OpenAI's Environmental, Health & Safety (EHS) team partners across the company to enable safe, responsible growth. This role will be a senior EHS partner to our robotics operations as our operating footprint expands. You will work closely with Robotics, Engineering, Operations, Facilities, Workplace, Construction, Security, People, Legal, and external partners to integrate safety into how our facilities are designed, built, staffed, and operated. About the Role We are seeking a Senior Manager, EHS - Robotics to provide senior, hands-on safety leadership across multiple sites. This role is for an experienced EHS leader who can operate independently in a fast-moving technical environment, anticipate risk before it becomes an incident, and build practical safety systems that scale with the business. Our robotics operations are scaling quickly, with a growing mix of construction, commissioning, workforce expansion, and around-the-clock operations. This creates a complex and evolving risk environment and requires strong preventive planning, consistent field presence, and sustained incident-management oversight. This leader will own site-level EHS strategy and execution for the robotics portfolio while partnering with the broader EHS team on company-wide standards and programs. The successful candidate will look around corners: planning for future ramps, identifying requirements early, influencing design and operating decisions, and creating durable systems that enable teams to move quickly without compromising safety. In this role you will: Serve as a senior EHS partner across robotics R&D operations, owning site-level safety strategy, priorities, and execution as the footprint scales. Anticipate EHS requirements for new operations, equipment, processes, construction phases, staffing ramps, and 24/7 operations, and translate them into practical plans before work begins. Lead proactive risk identification and control across robotics activities, incl

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE Baseten's engineers want to work in an AI-first way. What's missing isn't enthusiasm — it's the platform underneath it. Today everyone assembles their own agent config, context files, and MCP servers, so the good patterns stay trapped in individual setups instead of becoming defaults everyone inherits. You'll build that platform: the agent configurations tuned to our monorepo, the context and tooling layer that makes agents competent in our codebase, the evals that tell us which approaches actually work, and the rollout mechanics that get a new engineer productive with agents in week one. You are not here to mandate how engineers use AI — you're here to make the good path the easy path. Success looks like teams adopting what you build because it beats what they'd cobble together themselves, not because a policy requires it. Platform engineer, not AI evangelist. Ship infrastructure, measure it, kill what doesn't work, let adoption be the referee. The playbook for AI-first SDLC doesn't exist at any company yet. You'll write ours. WHAT YOU'LL BUILD Agent substrate — Repo-level context infrastructure that makes agents competent in our codebase ( CLAUDE.md/AGENTS.md conventions, architecture and domain context, and the tooling to keep it accurate as code moves). Internal MCP servers giving agents scoped access to CI, observability, incident tooling, deployment state, and docs. Shared skills, subagents, and hooks th

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE Baseten is building its own GPU infrastructure for large-scale inference. As we move into large scale, high-density NVIDIA systems, the hardest failures are intermittent, cross-layer, and difficult to prove: RoCE congestion, InfiniBand stalls, ECN/DCQCN mis-tuning, bad optics, RNIC issues, host kernel stalls, GPU driver problems, and workload symptoms that look like network problems, but are not. We are hiring a Lead Software Engineer to build a first-class observability and root-cause analysis system for GPU fabrics. This is a hard distributed systems problem, not a dashboarding problem. The system will collect high-volume signals from switches, hosts, active probes, and inference services; reduce and correlate them in real time; understand topology and service ownership; and produce actionable diagnosis while an incident is still unfolding. This role sits at the boundary between networking and inference software. RDMA data paths, GPUDirect transfers, prefill/decode disaggregation, KV cache movement, request routing, and workload backpressure can all create fabric symptoms or hide real fabric failures. The goal is to tell an operator, quickly and with evidence, whether an incident is caused by the fabric, host, NIC, GPU, RDMA path, scheduler, or serving layer — and what to do next. EXAMPLE INITIATIVES Real-time telemetry engine — Build the ingestion, reduction, storage, and query path for high-cardinality fab

About the Team The Industrial Compute team is responsible for building the physical infrastructure that powers OpenAI’s largest-scale AI systems. We design, deploy, and operate next-generation compute infrastructure across a rapidly expanding global footprint, combining OpenAI-owned infrastructure with strategic cloud and infrastructure partners to support frontier AI workloads. As our infrastructure footprint grows, operational excellence across third-party providers becomes increasingly critical. Our team ensures external infrastructure partners consistently deliver the reliability, performance, and operational maturity required to support OpenAI’s rapidly expanding compute environment. About the Role We are seeking a Hardware Technical Program Manager, Infrastructure Partner Operations to lead operational delivery across OpenAI’s third-party infrastructure partners, including major cloud service providers and strategic compute vendors. In this role, you will serve as the primary operational program manager for external infrastructure partners, driving accountability for service delivery, operational readiness, incident management, performance reporting, and continuous operational improvement. You will work closely with partner engineering and operations teams while coordinating internally across Hardware Engineering, Infrastructure Operations, Capacity Planning, Networking, Supply Chain, Deployment, Reliability Engineering, and executive leadership. Success in this role requires someone who understands how hyperscale infrastructure organizations operate, can establish strong operational governance with external partners, and is comfortable driving complex technical programs without direct ownership of the underlying infrastructure. Key Responsibilities Own operational engagement with third-party infrastructure providers, ensuring consistent execution against operational commitments, service-level agreements (SLAs), and performance expectations. Develop operationa

About the Team The Applied team brings OpenAI’s technology to the world through products used by hundreds of millions of people and by developers and businesses building on our APIs. We work across research, engineering, product, policy, safety, and operations to deploy frontier AI systems responsibly and safely. The Trust & Safety Data Engineering team builds the data foundations that help OpenAI understand, detect, investigate, and mitigate abuse and safety risks across our products. We partner with Integrity, Investigations, Safety Systems, Product Policy, Privacy, Data Science, Engineering, and Data Platform to create reliable, privacy-safe datasets and pipelines for fraud and abuse detection, enforcement workflows, safety measurement, ML feature generation, launch readiness, and transparency reporting. About the Role We are hiring a Technical Lead Manager to lead and grow the Trust & Safety Data Engineering team. This is a hands-on leadership role for someone who can set strategy, shape data architecture, align senior stakeholders, coach engineers, and drive execution on high-impact data systems. You will help turn fragmented launch and incident support into durable, reusable, privacy-safe data foundations that Trust & Safety teams can rely on. The systems your team builds will help OpenAI detect risk, investigate abuse, power operational workflows, develop and evaluate safety models, measure interventions, support product launches, and report accurately on platform integrity. In This Role, You Will Lead and grow a high-performing Trust & Safety Data Engineering team. Define the roadmap and technical strategy for Trust & Safety data systems. Build canonical, privacy-safe datasets and pipelines for abuse detection, fraud detection, risk signals, enforcement, scaled review, transparency reporting, and safety monitoring. Create reusable foundations for Trust & Safety model development, including features, labels, training data, backtesting,

About the Team The Online Data team builds and operates the core online database and indexing services for OpenAI’s production AI applications, including supporting the explosive growth of ChatGPT, the #1 AI app in the world, and Codex, the fastest growing agentic development toolset in the world. Our mission is to ensure the reliability, correctness, and scalability of our online data stack and to curate a comprehensive portfolio of services that matches the relentless ambition of OpenAI, enabling our product and research teams to build 0-100 without getting bogged down in the minutiae of multi-region, multi-cloud, exabyte-scale data infrastructure. About the Role We are seeking an Engineering Manager to lead our Online Data Systems team, responsible for our in-house database and indexing technology. This role is about shepherding a team of world-class engineers tasked with building and operating hyperscale data storage and retrieval technology. You’ll be overseeing the delivery of extremely challenging engineering work in areas like distributed query execution, multi-region federation, self-orchestrating and self-healing services, low-level performance optimization, and more. There are few companies in the world building this kind of technology in-house at this scale where you’ll still be getting in on the ground floor. Instead of being a cog in the machine spending months chasing small optimizations, you’ll play a major part of shaping our future. In this role, you will: Build, lead, and grow high-performing infrastructure engineering teams. Drive the evolution of OpenAI’s in-house online data technologies, our core, hyper-scale database systems, indexing technologies, and vector search. Anchor delivery around measurable reliability goals (SLOs, etc) to ensure system performance and resiliency is above reproach. Champion pragmatic use of agent technology to amplify execution velocity. Reduce operational toil and incident frequency through better abstractions, gua

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 Team OpenAI’s User Operations team shepherds our customers’ adoption of AI and ensures that our customers' product experience is nothing short of exceptional. We are building the very first post-AGI support team. We resolve complex issues, provide technical guidance, and support customers in maximizing value and adoption from deploying our products. We work closely with Sales, Technical Success, Product, Engineering and others, to deliver the best possible experience to our customers at scale. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. Within Premium Support, Dedicated Support Engineers combine deep technical troubleshooting with an enduring understanding of our most strategic customers’ architectures, critical workloads, and business priorities. Through proactive reliability work, ownership during incidents, and AI-powered support capabilities, we help customers operate successfully as their use of OpenAI grows. About the Role We’re looking for a senior leader to build and scale our Dedicated Support Engineering function globally. You will define its strategy, build the team, and establish how we deliver technically rigorous, proactive support for customers running some of the most complex and consequential workloads on OpenAI. This role combines organizational leadership, technical judgment, and executive customer engagement. You will establish a model in which DSEs develop deep customer context, independently advance difficult investigations, anticipate operational risks, and drive issues through resolution. You will also turn what the team learns into improvements that benefit customers across OpenAI. You should bring experience building technical organizations that maintain long-term accountability for enterprise customers. Leadership in Technical Account Management, enterprise Support Engineering, or a comparable technical customer function is particularly rel

About the Team The Agent Safety team works to ensure that increasingly capable AI agents act safely, exercise sound judgment, and remain aligned with user intent. Our mission is to reduce the probability of severe unintended outcomes from increasingly capable AI agents while preserving their ability to act effectively and autonomously. Our work spans three areas: Training: Create training methods, environments and data that teach agents to make better decisions in consequential situations. We turn real-world failures into training signals that prevent similar incidents, and identify precursor behaviors and mitigations to address emerging risks. Measurements: Build evaluations and production metrics that identify emerging risks and measure whether our interventions work. Oversight: Develop oversight and system mitigation mechanisms that reduce harmful actions while preserving useful autonomy (for example future versions of auto-review ). About the Role We’re looking for strong executors with excellent judgment, comfort with ambiguity, and an understanding of frontier model research. You don’t need prior safety or alignment experience, we also welcome people that recently realized that alignment and safety is a critical area to contribute to. 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: Train and evaluate frontier models to reduce harmful or misaligned agent actions, forming clear hypotheses and executing independently through ambiguity. Mine incidents and build scalable measurement, data-processing, and evaluation systems that turn real failures into repeatable safety signals. Collaborate closely with post-training, capabilities, oversight, and pre-training partners to ship research-backed mitigations into large-scale training and agent systems. You might thrive in this role if you: Have demonstrated strength in research engineering, ML en