Engineering Architect in United States

About the Team The Core Models team helps shape how OpenAI’s frontier models are built, measured, and launched. We work across Research, Engineering, Model Design, Data Science, and Product to turn advances in model capabilities into reliable, useful experiences for people. Our scope includes model planning and launches as well as building data flywheels, evaluations and measurement systems to ensure our models have strong capabilities and behavior. About the Role As a Product Manager for the Core Models team, you'll be at the forefront of defining and guiding the future of how our AI models work in real-world applications. You will connect user needs to model and systems decisions: how prompts are understood; how information is aggregated and made useful for training and evaluation data; and how capabilities move from research prototypes into the mainline model and launch stack. You will operate comfortably across research, infrastructure, and consumer product surfaces, creating clarity where ownership and technical boundaries are still emerging. 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: Translate user and product goals into clear model requirements, system architecture choices, and research priorities across query understanding, indexing, retrieval, ranking, tool boundaries, data, training, inference, and evaluation. Build closed learning loops that turn product usage, explicit feedback, and other user signals into datasets, evaluations, experiments, training priorities, and launch decisions. Define success across offline evaluations and online product metrics, balancing model quality, usefulness, latency, safety, reliability, and cost. Partner closely with post-training research, applied product engineering, Model Design, and Data Science to integrate capabilities into the mainline model stack. Create reusable platforms and operatin

About the Team OpenAI's research training infrastructure powers how our frontier models are trained and evaluated. The Simulation team sits at the intersection between the agentic harness that powers OpenAI's products and the research infrastructure where GPT-next is trained, ensuring that our model's training environment is as realistic as possible. This team owns the integration layer that connects our production harness capabilities into the training stack. The work is highly cross-functional and high leverage: researchers depend on it to run experiments and evaluations reliably as well as to develop the next generation of harness capabilities. Failures in this surface can materially affect training velocity and correctness. About the Role We're looking for a Principal Software Engineer to lead the architecture and evolution of the Simulation Platform. You'll own a critical interface between research and engineering, building the systems, APIs, and operational patterns that let researchers use agentic coding infrastructure safely and effectively in training environments. This role is ideal for a senior backend or infrastructure engineer with strong technical judgment, product sense for highly technical users, and the ability to drive execution across multiple teams. The highest-leverage work is building robust infrastructure that supports and accelerates research without compromising engineering quality. In this role, you will Design, build, and evolve the integration between the Codex harness that powers OpenAI's products and research training infrastructure used for training GPT-next Build a platform for our LLMs to train and be evaluated in simulated environments that mimic their deployment setting as closely as possible, on every axis: agentic harness, compute substrate, timing, tools, data sources, humans in the loop, and more Own major integration surfaces end-to-end, from architecture and API design through rollout, operations, and long-term maintenance Bu

About the Team The Pricing & Monetization team is responsible for how our products create and capture value. We partner closely with Product, Engineering, Data Science, GTM, and Finance to design pricing models, packaging, and commercial strategies that support adoption, growth, and long-term scaling of the business. To thrive in this team, you need to be a proactive problem-solver who excels at bringing structure to ambiguous challenges. Our work demands strategic thinking, cross-functional collaboration, and precision in execution. Team members succeed when they are analytical, detail-oriented, skilled at balancing multiple priorities, and passionate about driving high-stakes projects forward to deliver meaningful results. About the Role We are looking for a Pricing Strategist to shape how we price and monetize OpenAI’s API platform. You’ll own the end-to-end pricing strategy across model launches, price architecture, packaging, commitments and discounts, and monetization guardrails. You’ll work closely with senior leaders across Product, Engineering, Data Science, GTM, and Finance to define pricing approaches, improve commercial decision-making, and bring more rigor to how we monetize our API offerings. You should be comfortable building monetization frameworks and commercial policies, analyzing tradeoffs, supporting high-impact decisions and driving decision making. You should also care deeply about the customer perspective and believe that strong pricing reflects a real understanding of customer value, needs, and friction points in order to build pricing that is clear, fair, and aligned with how customers experience our products. This role will report to the Head of Product Pricing for API & Platform. What you’ll do Develop the end-to-end pricing strategy for our API platform, including model launch pricing, price architecture, packaging, discount logic, and monetization guardrails. Recommend pricing for new models, capabilities, and platform offerings,

About the Team Data Platform at OpenAI owns the foundational data stack powering critical product, research, and analytics workflows. We operate some of the largest Spark compute fleets in production; design, and build data lakes and metadata systems on Iceberg and Delta with a vision toward exabyte-scale architecture; run high throughput streaming platforms on Kafka and Flink; provide orchestration with Airflow; and support ML feature engineering tooling such as Chronon. Our mission is to deliver reliable, secure, and efficient data access at scale and accelerate intelligent, AI assisted data workflows. Join us to build and operate these core platforms that underpin OpenAI products, research, and analytics. We’re not just scaling infrastructure – we’re redefining how people interact with data. Our vision includes intelligent interfaces and AI-assisted workflows that make working with data faster, more reliable, and more intuitive. About the Role This role focuses on building and operating data infrastructure that supports massive compute fleets and storage systems, designed for high performance and scalability. You’ll help design, build, and operate the next generation of data infrastructure at OpenAI. You will scale and harden big data compute and storage platforms, build and support high-throughput streaming systems, build and operate low latency data ingestions, enable secure and governed data access for ML and analytics, and design for reliability and performance at extreme scale. You will take full lifecycle ownership: architecture, implementation, production operations, and on-call participation. You’ve supported Spark, Kafka, Flink, Airflow, Trino, or Iceberg as platforms. You’re well-versed in infrastructure tooling like Terraform, experienced in debugging large-scale distributed systems, and excited about solving data infrastructure problems in the AI space. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per wee

About the team The Applied team safely brings OpenAI's technology to the world. We released ChatGPT; Plugins; DALL·E; and the APIs for GPT-5, embeddings, and fine-tuning. We also operate inference infrastructure at scale. There's a lot more on the immediate horizon. Our customers build fast-growing businesses around our APIs, which power product features that were never before possible. ChatGPT is a prime example of what is currently possible. We simultaneously ensure that our powerful tools are used responsibly. Safe deployment is more important to us than unfettered growth. The Fraud Engineering team works within our Applied Engineering organization identifying and responding to fraudsters on our platform. We are looking for a software engineer with anti fraud & abuse experience to help architect and build our next-generation anti-fraud systems. About the role The Scaled Abuse team protects OpenAI’s products and customers by detecting, preventing, and responding to fraudulent and abusive behavior at scale. We build and operate the backend and data systems that power real-time detection, investigation workflows, and enforcement — balancing strong protections with a great user experience as the platform grows. Our work sits at the intersection of engineering and abuse expertise: we partner closely with Trust & Safety, Security, and Product to understand emerging attack patterns, translate messy signals into clear system behavior, and continuously harden our defenses. The problems are dynamic and ambiguous by default, so we value engineers who can quickly dive into an unfamiliar codebase, develop strong intuition about how it works end-to-end, and propose pragmatic improvements that make the entire stack more resilient. In this role, you will: Design and build systems for fraud detection and remediation while balancing fraud loss, cost of implementation, and customer experience Work closely with finance, security, product, research, and trust & safety ope

About the Team OpenAI Finance is responsible for ensuring the organization is set up for success in pursuit of its mission. OpenAI’s Tax and Trade team sits at the center of OpenAI’s global growth—shaping how cutting-edge AI products, partnerships, and infrastructure scale across borders while navigating complex tax, trade, and regulatory regimes. We operate as strategic operators, not just compliance experts, embedding early in product, finance, policy, and infrastructure decisions to manage risk, unlock incentives, and enable OpenAI to grow responsibly and competitively worldwide. As OpenAI’s products, monetization models, and global infrastructure expand, our tax systems must scale with the same rigor and reliability as our product architecture. The team partners deeply with Financial Engineering, Product Engineering, and Finance Systems to build a modern tax technology stack that enables accurate, real-time tax determination across OpenAI’s global business. About the Role We're hiring a Director, Tax Infrastructure & Incentives to lead OpenAI's global tax infrastructure strategy supporting AI infrastructure expansion programs. You will own the tax strategy supporting data center development, site selection, infrastructure investments, and government incentive programs across. This role extends far beyond traditional property tax planning and reporting - you will help shape where and how OpenAI invests billions of dollars in AI infrastructure by partnering with executive leadership, infrastructure teams, governments, utilities, and external stakeholders. You will build scalable frameworks for negotiating and managing tax incentives, property tax, indirect tax, and infrastructure-related tax matters while developing repeatable processes that enable OpenAI to expand rapidly across multiple jurisdictions. You will also establish the governance, reporting, and operational infrastructure required to support long-term compliance, financial reporting, and executive

About the Team The Statsig team at OpenAI builds and operates the experimentation platform that powers product development, measurement, and decision-making across the company. We partner closely with product, engineering, and infrastructure teams to ensure experiments are trustworthy, statistically rigorous, and scalable to the needs of frontier AI products. Our mission is to help teams make better decisions through reliable experimentation. We care deeply about statistical correctness, pragmatic solutions, and building systems that researchers and engineers can trust at massive scale. The team operates at the intersection of experimentation methodology, data infrastructure, causal inference, and product analytics. We are looking for experienced experimentation experts who want to shape the future of experimentation in the AI era. About the Role We are hiring a Staff-level Data Scientist to help lead the evolution of OpenAI’s core experimentation platform. This role is focused on improving the statistical rigor, reliability, and practical usability of experimentation across the company. You’ll work on some of the hardest problems in online experimentation: sample ratio mismatch detection, variance reduction, bias mitigation, metric design, triggered analysis, heterogeneous treatment effects, sequential testing, and experimentation in complex ML systems. You’ll also help translate advanced statistical concepts into pragmatic systems and product experiences that teams can actually use. This is a highly technical individual contributor role with significant influence across methodology, platform architecture, and experimentation best practices. The ideal candidate combines deep statistical expertise with strong systems intuition and hands-on experience building or operating experimentation platforms at scale. In this role, you will: Drive the statistical direction and technical strategy for OpenAI’s experimentation platform Design and improve experimentation methodolo

About the Team Our Inference team brings OpenAI’s most capable research and technology to the world through our products. We empower consumers, enterprise and developers alike to use and access our start-of-the-art AI models, allowing them to do things that they’ve never been able to before. We focus on performant and efficient model inference, as well as accelerating research progression via model inference. About the Role We are looking for an engineer who wants to take the world's largest and most capable AI models and optimize them for use in a high-volume, low-latency, and high-availability production and research environment. In this role, you will: Work alongside machine learning researchers, engineers, and product managers to bring our latest technologies into production. Work alongside researchers to enable advanced research through awesome engineering. Introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of our model inference stack. Build tools to give us visibility into our bottlenecks and sources of instability and then design and implement solutions to address the highest priority issues. Optimize our code and fleet of Azure VMs to utilize every FLOP and every GB of GPU RAM of our hardware. You might thrive in this role if you: Have an understanding of modern ML architectures and an intuition for how to optimize their performance, particularly for inference. Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done. Have at least 5 years of professional software engineering experience. Have or can quickly gain familiarity with PyTorch, NVidia GPUs and the software stacks that optimize them (e.g. NCCL, CUDA), as well as HPC technologies such as InfiniBand, MPI, NVLink, etc. Have experience architecting, building, observing, and debugging production distributed systems. Bonus point if worked on performance-critical distributed systems. Have need

About the Team Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role We are seeking a Lead Robotics Safety Engineer to define and lead the product safety strategy for our robotics program. You will work closely with leadership, engineering, research, legal, and policy teams to ensure safety is integrated into our products from the earliest stages of development through deployment. This role combines product safety, regulatory strategy, systems engineering, and risk management. You will help shape how we think about safety across robotic platforms, influence product architecture and development decisions, and ensure our systems are designed to meet both current and emerging regulatory expectations. You will serve as a subject matter expert on robotics safety standards, regulatory frameworks, and safety engineering practices while helping establish the long-term safety strategy for our products and organization. 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 Define and lead the product safety strategy for robotic systems across the development lifecycle. Monitor and influence emerging regulatory frameworks, industry standards, and policy developments relevant to robotics and autonomous systems. Partner with engineering teams to translate safety requirements into product architecture, design decisions, and engineering requirements. Develop and maintain system-level hazard analyses, risk assessments, and safety cases for robotic products. Establish safety requirements, verification strat

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role You will develop and evolve the tooling ecosystem that hardware engineers rely on every day — from hardware compilers and IR transformations to simulation, debugging, and automation infrastructure. The work spans software engineering, compiler concepts, and practical hardware workflows, with direct impact on how quickly and effectively we design next-generation AI systems. You’ll collaborate closely with architects, RTL designers, and verification engineers to translate real engineering friction into durable, scalable tooling solutions. In this role you will: Build and improve the software tooling that makes hardware teams faster: compilation, IR transforms, RTL generation, simulation, debug, and automation. Extend and integrate hardware compiler stacks (frontends, IR passes, lowering, scheduling, codegen to Verilog/SystemVerilog) and connect them to real design workflows. Improve developer experience and reliability: reproducible builds, better error messages, faster iteration loops, and dependable CI and regression infrastructure. Work closely with designers and verification engineers to turn real pain points into durable tools. Dive into RTL when needed: read and reason about Verilog/SystemVerilog to debug issues, validate tool output, and improve debuggability. Be willing to go all the way down the stack when necessary, including gate-level views, synthesis results, and implementation artifacts. Help enable PPA optimization loops by building analysis and au

About the Team The Support team is central to ensuring that our customers' experience with our products is nothing short of exceptional. 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. Given OpenAI’s breakneck shipping cadence and growth – and the expectation that it will only accelerate – our ability to architect automation systems and agentic workflows for scale is central to our ability to maintain exceptional support quality in the face of AGI. About the Role As a Support Vendor Manager, you will own the health, performance, and long-term scalability of multiple support partner and vendor relationships. This is a vendor leadership role first and foremost: you will drive commercial and operational accountability (SLAs, QBRs, escalation paths, remediation plans), while also building the operating model that enables support to scale without linear headcount growth. You’ll collaborate closely with User Operations teams (e.g., Trust & Safety, Fraud & Risk), Systems/Tooling, Data partners, and Product/PM stakeholders as we launch new workflow and launch and scale new programs. You’ll be responsible for: End-to-end vendor leadership: Own day-to-day oversight, relationship health, and executive-level accountability for multiple support vendors/BPOs. Performance management & remediation: Define and manage SLA/KPI performance expectations, run WBRs/QBRs, identify performance gaps, and drive structured turnaround plans with clear owners and timelines. Escalation and risk management: Serve as the primary escalation point for vendor issues, including incident response, surge events, quality regress

About the Team The Personalization-Memory team, within OpenAI's broader Personal AGI organization, is focused on developing agents that can learn from prior interactions in order to become more helpful and efficient over time. We build general-purpose memory and personalization capabilities that transfer across ChatGPT and other agentic products, and we collaborate with applied engineering on the product surfaces that allow users to interact with memory. About the Role As a Research Engineer / Research Scientist on the Personalization-Memory team, your work will span memory architecture, post-training, and developing long-horizon tasks for training and evaluations. We're looking for individuals who have a background in reinforcement learning research, are able to iterate quickly, and who can convert scientific rigor and long-term research into realized product impact. 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 and pursue a research agenda for improving long-horizon memory and personalization in frontier models. Build robust evaluations for tracking modeling improvements. Design, implement, test, and debug code across our research stack. Collaborate closely with the research and product teams to influence the shape of technical solutions in the product. You might thrive in this role if you: Love being on the cutting edge of RL and frontier model research. Value principled approaches and research craftsmanship. Are passionate about long-horizon tasks, memory, and turning your research into product impact. Are comfortable diving into a large ML codebase to debug. Thrive in a fast-paced, dynamic, and technically complex environment. 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 syst

Where Performance Meets Purpose Join a team that values excellence and innovation, at a company known for its iconic golf brands. At Acushnet Company, your background and experience contribute to creating the best products for dedicated golfers worldwide. Here, your performance has purpose. What You Will Be Doing We’re seeking a data-driven and collaborative Lead Digital Technology & Marketing Analytics professional to help transform data into actionable business insights across digital, marketing, operations, and enterprise functions. In this role, you’ll work closely with stakeholders across digital marketing, customer service, operations, engineering, R&D, and IT to support the integration, management, and analysis of data from a variety of sources. You will be responsible for developing, testing, and maintaining dashboards, reports, visualizations, and self-service analytics solutions that enable business users to make informed decisions and support strategic initiatives. Partnering with centralized data and technology teams, you’ll help define data architecture, manage data pipelines, validate datasets, develop data models, and support data governance best practices across the organization. As a key member of the analytics function, you will drive adoption of analytics tools through user training and enablement, collaborate on prioritizing business requests, and contribute to test-and-learn initiatives including A/B testing and incremental analysis. Your ability to identify trends, uncover opportunities, and communicate insights clearly will play a critical role in advancing data-driven decision making across the business. What You Bring · Bachelor’s degree in Data Science, Computer Science, Business, Econo

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary We are hiring a Senior Full Stack Software Development Engineer with strong React and Python (with .NET as a nice-to-have) experience to join our Data Engineering team. You will serve as a key senior contributor, driving the end-to-end development of a new, critical internal self-service application. Your work on this software solution will be instrumental in our initiative to modernize how data is accessed and managed, enabling teams across the company to more easily work with their own data through the user-friendly tools you build. This project involves a shift from traditional data handling processes, with your primary focus being on creating a robust application that empowers this new approach to data accessibility and decentralized ownership. About this Role: This is a high-impact, high-autonomy role suited for a detail-oriented and collaborative individual who thrives on ownership, knows how to apply best practices, and can independently design, build, and maintain production-grade software. While you'll be leveraging your core software engineering expertise, you'll also be at the forefront of our data modernization, gaining deep insights into modern data architectures and practices by building the tools that enable them. You will have access to AI tooling to assist in all aspects of the SDLC. Y

Leidos is looking for our next TS/SCI-cleared Elastic Search Engineer to join a high-energy team building and deploying a cutting-edge technology stack to support our client’s mission to centralize and standardize Tasking, Collection, Processing, Exploitation and Dissemination (TCPED) of Open Source Intelligence (OSINT) across the DoD and IC enterprise. We integrate off the shelf and newly development software to sustain and enhance the TCPED platform. We leverage cloud-based computing, artificial intelligence (Al), machine learning (ML) and cross-domain transfer systems to provide cutting edge data exploitation, enrichment, triage, and analytics capabilities to Defense and Intelligence Community members. DTP advances the state of the art in mission-focused big data analytics tools and micro-service development spanning the breadth of Agile sprints to multiyear research and development cycles. As an Elastic Search Engineer, you’ll be a member of our platform engineering team and help develop, deploy and maintain nosql databases as foundational elements of our microservice eco-system using a Kubernetes as foundational platform. You’ll also support the adoption of GitOps best practices across cross-functional engineering teams. In this fast-paced environment, you’ll collaborate closely with systems engineering, architecture, development, security, operations, and integrations teams. Work is conducted on-site at our client location in Bethesda, MD. Key Responsibilities Include: Deploy, triage, debug, and maintain production class databases like Elasticsearch and Redis Design and support database configuration management strategies across air-gapped network fabrics Partner with Systems Engineers to architect solutions for new capabilities Contribute to operational monitoring capabilities to provide proactive system notifications Contribute technical input to engineering documentati