Software Engineer Distributed Systems Salary India in United States

About the Team The Applied team at OpenAI safely brings cutting-edge technology to the world. We have released widely used products such as ChatGPT, Sora, and the OpenAI API, powering models including GPT-5 and a growing set of multimodal capabilities across text, image, audio, and video. Our team also manages large-scale inference and platform infrastructure that supports these experiences at global scale. With much more on the horizon, our impact continues to grow. Our customers build fast-growing businesses using our APIs, unlocking product capabilities that were previously unimaginable. ChatGPT and Sora exemplify the breadth of what’s now possible across text, image, audio, and video experiences. As these capabilities expand, we prioritize the responsible use of our technology, emphasizing safe and thoughtful deployment over unchecked growth. Within Applied Engineering, the Ads Monetization team in Financial Engineering builds the core systems dealing with all the money flows for ChatGPT Ads. These systems are a combination of low-latency, high scale, high reliability, while being built in a financially correct, accurate, auditable and explainable way. This role sits at the intersection of ads delivery, data engineering, and financial systems. In this role, you will: Architect and build the core monetization systems for ChatGPT Ads. Build and operate the core services and pipelines that power ads monetization end-to-end, from event capture and validation through aggregation, pricing, metering, and ultimately producing billable outputs. Define and implement the source of truth for ads monetization data, including schemas, data models, and invariants that ensure outputs are consistent, explainable, and auditable. Own correctness and reconciliation: align production outputs with downstream invoicing/finance requirements, build controls/monitors, and close gaps through investigations and backfills. Develop across the stack to create comprehensive billing integration

About the Team The Cooperative AI team is scaling OpenAI with OpenAI. We are building an AI powered knowledge system that evolves and learns as our products, systems and customers evolve. We leverage our state of the art models, technologies, and products (some external, some still in the lab) to assist or completely automate robust operations supporting both internal and external customers. We support OpenAI customers and internal partners globally, powering systems from customer support to integrity to product insights. We are a self-contained multi-disciplinary team, who enjoy a lightning fast feedback loop with customers at scale, some of whom sit just a few pods away. We iterate fast, and engineer for reliable long-term impact. We're constantly looking for the similarities and patterns in different types of work, and focus on building simple primitives, to apply world class knowledge to many domains. The work of this team exemplifies use of OpenAI technologies. We build systems so everyone can see the leverage that is possible with well designed AI-based implementations. We do this by working through internal use cases focused on Customers (specifically knowledge systems, automation systems, and automated agent systems) to prove impact, then we scale. About the Role We’re looking for Software Engineers who're passionate about blending production-ready platform architecture with new tech and new paradigms. You’ll push the boundaries of OpenAI’s newest technologies to enable interactions and automations that are not only functional, but delightful. We value proactive, customer-centric engineers who can get the foundational details right (data models, architecture, security) in service of enabling great products. In this role, you will: Own the end-to-end development lifecycle for new platform capabilities and integrations with other systems Collaborate closely with engineers, data scientists, information systems architects, and internal customers to understand th

About the Team ChatGPT is a rapidly evolving system: new capabilities ship continuously, product surfaces change quickly, and usage patterns shift week-to-week. Supporting that pace requires infrastructure that can handle real production constraints—high concurrency, unpredictable traffic patterns, complex dependency graphs, and frequent change. The ChatGPT Infrastructure team builds and operates the platforms that enable fast iteration without compromising performance or reliability. We design shared systems, data paths, rollout mechanisms, and reliability guardrails that teams rely on to ship changes to ChatGPT at scale. We focus on high-leverage infrastructure: primitives and “golden paths” that incorporate operational lessons as defaults, so engineers don’t need to rediscover failure modes, latency pitfalls, or integration issues each time they build something new. About the Role We’re hiring Senior and Staff Engineers to design and build infrastructure systems that underlie ChatGPT and multiply the effectiveness of teams building user experiences. This is not a support-only role. It’s a platform-building role: you’ll define interfaces, develop core abstractions, and create tooling to make safe, fast iteration the norm. Your work will reduce friction, prevent regressions, improve performance, and ensure systems scale gracefully as the product grows. Where You Can Have Impact You might work on one or more of the following areas (without being restricted to any single area): Platform foundations & frameworks: Core libraries, service frameworks, and shared components that standardize system building, integration, and evolution. Scalability & performance primitives: Patterns and infrastructure that reduce tail latency, improve throughput, and keep costs predictable as demand increases. Reliability guardrails: Mechanisms that prevent outages by design—rate limiting, load shedding, dependency isolation, backpressure, safe fallbacks, and robust regression contr

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 an experienced Software Engineer to help build the core monetization and ads systems at OpenAI. This is a foundational role responsible for designing and implementing the infrastructure, APIs, and user-facing experiences that will power OpenAI’s next-generation monetization products—including ads. You’ll work across the full technical stack to architect, build, and ship 0→1 systems that are robust, safe, and scalable. You will collaborate deeply with Product, Design, and Research to define the future of monetized AI experiences and ensure these systems meet OpenAI’s highest standards for safety, privacy, and policy alignment. This role is exclusively based across our San Francisco and Seattle sites. We offer relocation assistance to new employees. In this role, you will: Design, build, and scale the core infrastructure behind OpenAI’s monetization and ads products Develop advertiser-facing APIs and tools that enable the cre

About the Team GTM Growth Engineering builds AI-native products and systems that help OpenAI's go-to-market and B2B marketing organizations operate with greater speed, focus, and leverage. Our mandate is revenue leverage: products tied directly to pipeline quality, customer engagement, seller and marketer productivity, and the speed at which OpenAI can bring its technology to customers. We build the infrastructure and user experiences behind high-impact GTM workflows, including customer context, prioritization, routing, campaign execution, review surfaces, feedback loops, and measurement. Our work combines product craft, applied AI, reliable systems, and thoughtful operational design. About the Role We’re looking for a product-minded Software Engineer to build AI-powered products and full-stack experiences for GTM Growth Engineering. You will own meaningful product slices end to end, from user experience and frontend implementation to backend APIs, integrations, data models, instrumentation, and launch readiness. This is a role for engineers who want to build products that do real work in production. You will partner with Product, Design, Data Science, Sales, B2B Marketing, and operations teams to understand high-value workflows and ship systems that improve customer engagement, pipeline, conversion, and team productivity. The role is ideal for a strong product engineer who can move between product craft, systems engineering, applied AI, and measurable business outcomes. You should be excited to build from ambiguous problem statements, ship quickly, and improve products based on real user feedback. What You'll Do Build AI-powered products and workflows that help sales and B2B marketing teams identify opportunities, coordinate work, and engage customers more effectively. Own full-stack product experiences from prototype through launch, instrumentation, iteration, and production hardening. Design intuitive user journeys that combine polished interfaces, reliable servi

About the Team With Codex we’re building an AI software engineer. One that you can pair with, delegate to, or even ask to take on future tasks proactively. Our team is a fast-moving group within OpenAI, bringing together research, engineering, design, and product. We iteratively build the Codex agent harness and product to get the most out of the model, and we iteratively train the model to be great at complex software engineering tasks. The Codex team is responsible for building state-of-the-art AI systems that can write code, reason about software, and act as intelligent agents for developers and non-developers alike. We operate across research, engineering, product, and infrastructure; owning the full lifecycle of experimentation, deployment, and iteration on novel coding capabilities. Codex Enterprise builds the ecosystem building blocks, discovery surfaces, and enterprise capabilities that help Codex spread across developers, teams, and organizations worldwide. It is a cross-cutting team that works across the stack to build both delightful product experiences and fundamental platform capabilities. Its customers range from individual developers and small teams to large enterprises, and our mission is critical to achieving the vision of Codex as a proactive teammate. About the Role As we grow, we’re focused on turning Codex from a powerful individual tool into a production-grade teammate for entire organizations. You will work across internal OpenAI teams and external customers, from fast-moving startups to large enterprises, to make it possible to deploy, operate, and trust Codex in increasingly demanding real-world environments. As Codex’s consumer adoption accelerates, enterprise demand is growing just as quickly, and there is also increasing opportunity to expand Codex through ecosystem capabilities that unlock new workflows, integrations, and discovery. This team helps turn messy, real-world team requirements into robust, repeatable, and scalable product and

About the Team OpenAI’s mission is to ensure that artificial general intelligence benefits all of humanity. A majority of our users interact with our products in languages other than English, and our products must work seamlessly across languages, regions, and cultures. The Internationalization team builds the infrastructure that enables OpenAI products to ship globally by default. We develop the systems that power localization, international product launches, and high-quality global user experiences across all OpenAI products. About the Role As a Senior Software Engineer on the Internationalization team, you will build the systems that power localization and international product launches at OpenAI. You’ll work on the platform that manages product content, translation workflows, and localization infrastructure across our products. This role sits at the intersection of AI systems, developer platforms, and product infrastructure. In this role, you will Build and scale OpenAI’s localization, content, and experimentation platform used across OpenAI product teams, including open-source components: Develop AI-powered translation pipelines combined with human-in-the-loop review workflows. Design systems that reliably deliver localized product content across web and mobile apps. Build tools that enable linguists and localization teams to review and improve translations. Develop developer tooling that simplifies localization and internationalization workflows. Build and maintain internationalization libraries used across OpenAI products: Design systems that correctly handle numbers, currencies, dates, and pluralization across locales. Improve support for multilingual interfaces and right-to-left languages. Partner with product teams to improve the international readiness of new features. You might thrive in this role if you Have strong software engineering experience building backend or full-stack systems. Have familiarity with Java, React, MySQL, and cloud infrastructure p

About the Team The Platform Analytics team builds the systems OpenAI researchers use to understand the quality and behavior of the models we train including what models are doing, why they behave in a particular way, and how that behavior changes across experiments. Neptune is a core part of this work. It ingests, stores, queries, and visualizes large volumes of metrics from pretraining, post-training, and reinforcement learning. Hundreds of researchers depend on these systems in their daily work to compare experiments, debug unexpected behavior, and decide what to try next. Our scope is broader than metrics. We also build platforms that help researchers analyze samples, traces, evaluation results, and other structured or unstructured data through dashboards, APIs, and increasingly agent-driven workflows. These systems need to remain fast, reliable, and understandable as the scale and complexity of research change quickly. We are not trying to become a consulting team that builds a separate solution for every research project. We work directly with researchers to understand recurring problems, then turn them into reusable infrastructure and platform capabilities that many teams can build on. About the Role We’re looking for a hands-on experienced software engineer who can take ownership of a critical system and drive it from problem definition through production adoption. This person should be able to own a platform such as CacheHouse end to end: define its technical direction, design its data model and storage architecture, integrate it with several research dashboards and workflows, guide one or two engineers, and ensure the system works reliably for its users. The right candidate should already bring the technical judgment, ownership, and execution expected at this level. The primary learning curve should be OpenAI’s stack and research problem space, not learning how to lead a complex engineering effort or deliver a production system. You will work directly with

About the Team The Statsig team within OpenAI owns the experimentation, rollout, dynamic configuration, and analytics infrastructure that sits on the launch path for OpenAI products. Our systems help teams ship safely, evaluate product and model changes in production, and make high-confidence decisions from real-world usage. Statsig began as an independent company built around experimentation, feature management, and product analytics at scale. After Statsig joined OpenAI, the team began the next chapter: bringing that platform expertise and infrastructure into OpenAI as the experimentation and rollout foundation for every product we ship. This is infrastructure with a very direct product consequence. Teams working on ChatGPT, Codex, model measurement, consumer experiences including ads, business subscriptions, developer products, and shared platform systems depend on Statsig to evaluate configurations, move traffic safely, ingest experiment data, serve analytics, and roll changes forward or back when production reality demands it. We are at a critical point in the platform journey. Adoption is accelerating quickly across OpenAI, and the systems that were already important are becoming load-bearing for how the company launches. The infrastructure needs to stay fast under sharply increasing evaluation volume, reliable when more services depend on it, observable enough to debug quickly, and efficient enough to support OpenAI-wide scale. Recent SDK and server-side infrastructure work has already produced measurable wins in latency, reliability, memory usage, and compute efficiency across important services. The next phase is to make those gains systematic: a platform that can absorb rapidly growing product velocity while preserving low latency, data quality, operational safety, and developer trust. Based out of OpenAI's Bellevue office, we are a close-knit team that values in-person collaboration, technical depth, operational ownership, and building infrastructure that

About the Team We’re hiring software engineers to make OpenAI’s Model Performance teams more productive. These teams work on the systems, tooling, and infrastructure that help improve model performance across OpenAI’s training and inference workloads at frontier scale. About the Role We’re looking for an autonomous, high-ownership developer productivity engineer who cares deeply about helping other engineers move faster, safer, and with more confidence. This role will sit within OpenAI’s Model Performance organization, contributing to developer infrastructure, CI systems, testing workflows, tooling, and broader performance infrastructure efforts. There is also a strong opportunity to contribute to the Triton project and help improve the systems that support performance-critical engineering work across OpenAI. In this role you will: Improve development workflows for engineers working on model performance infrastructure Design and improve CI/CD, release, validation, and testing pipelines Build and maintain tools that improve reliability, iteration speed, and engineering confidence Partner closely with engineers to identify friction in testing, debugging, deployment, and development workflows Contribute to infrastructure efforts that support performance-critical training and inference systems Help improve developer experience across Python-heavy codebases and performance-oriented infrastructure Work in a high-context, ambiguous environment where ownership and good judgment matter You might thrive in this role if: You are motivated by enabling the people around you and helping engineers do their best work You have strong experience with CI/CD, developer infrastructure, testing systems, tooling, or build/release workflows You are highly collaborative, empathetic, and comfortable partnering deeply with technical teams You are strong in Python and enjoy building reliable, scalable developer tools and infrastructure You have experience improving large-scale engineering work

About the Team OpenAI’s Platform and Infrastructure Engineering organization advances the mission of deploying artificial general intelligence (AGI) for the benefit of all by delivering secure, scalable, and resilient technology solutions. Our team builds and maintains robust infrastructure that safeguards OpenAI’s data and systems while ensuring employees are well-equipped and seamlessly connected. By prioritizing security, reliability, and user-centric solutions, we empower OpenAI employees to drive impactful AI research, corporate operations, and product innovation. About the Role As a Software Engineer: Internal Applications, Enterprise, you will build internal products that make technology support and administration safer, faster, and less dependent on manual intervention. You will help reduce reliance on broadly privileged human actions, turn recurring technology problems into paved paths, and build agentic systems that can help resolve tickets end to end. A core part of the role is building the interfaces that bring employees, AI agents, and human responders together in a shared ITSM experience, with the right context, controls, and handoffs at each step. We are seeking engineers who enjoy working across frontend and backend layers on ambiguous, high-leverage enterprise problems. You should bring strong product judgment, solid backend engineering fundamentals, and an interest in building software that changes how technology support, system administration, and agent-assisted operations are delivered. The best fit will care as much about the quality of the operator and employee experience as the correctness of the backend systems behind it. In this role, you will: Build frontend experiences that let employees request help, let agents gather context and take safe actions, and let human responders review, approve, or take over without losing the thread. Reduce reliance on broadly privileged manual actions by replacing them with narrow, auditable, policy-aware aut

About the Team We’re hiring software engineers to make OpenAI’s networking teams more productive. These teams build and operate the high-performance networking systems that support OpenAI’s training and inference infrastructure at frontier scale. About the Role We’re looking for someone who cares deeply about the developer experience of engineers working on complex infrastructure systems — especially around build systems, test architecture, release pipelines, and reliable development workflows. This role will be embedded with OpenAI’s networking team: making it faster, safer, and easier for engineers to build, test, validate, and ship changes across multi-server, networked, and hardware-adjacent environments. In this role you will: Improve development workflows for engineers building and operating OpenAI’s networking systems Design and improve continuous deployment, release, and validation pipelines Build and maintain test harnesses for multi-server, networked, and hardware-backed environments Improve iteration speed across C++, Python, and build-system-heavy codebases Partner with engineers to identify friction in CI, testing, debugging, and deployment workflows Drive testing and reliability strategy for infrastructure components that support large-scale training and inference workloads Work closely with centralized developer experience teams while staying deeply embedded with the networking engineers closest to the systems You might thrive in this role if: You are motivated by helping other engineers move faster and with more confidence You have experience with CI/CD, release pipelines, testing infrastructure, or build systems You are comfortable moving between C++, Python, and build systems such as CMake, Bazel, or Blaze You enjoy building test harnesses, automation, and workflow improvements for complex systems You do not need to be a networking expert, but you are excited to learn enough about the domain to make the team meaningfully more effective When you see

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 We are looking for a systems-minded engineer to help advance our kernel development, performance engineering, and hardware-software co-design capabilities, with a particular focus on AI-assisted workflows and tooling. This person will work at the intersection of kernel optimization, developer tooling, observability, and research infrastructure, helping us improve both how production kernels are built and optimized, and how future hardware-software systems are designed and evaluated. The role is ideal for someone who is excited by low-level performance work, but also sees AI and automation as powerful tools for accelerating engineering velocity. You will help define the future of kernel engineering in the era of AI-assisted development. In this role, you may: Build developer tooling and workflows that make kernel development and performance optimization faster, more scalable, and easier to debug, integrate, and deploy. Develop observability, diagnostics, and validation infrastructure that makes AI-assisted optimization systems more interpretable, reliable, and effective. Optimize production kernels end to end by formulating optimization problems, running search loops, analyzing bottlenecks, debugging generated implementations, and landing improvements into production. Design abstractions, interfaces, and automation systems that accelerate kernel optimization, correctness validation, and hardware-software co-design. Improve AI-assisted optimization systems for sp

About the Team The Foundations Research team works on high-risk, high-reward ideas that could shape the next decade of AI. Our goal is to advance the science and data that enable our training and scaling efforts, with a particular focus on future frontier models. Pushing the boundaries of data, scaling laws, optimization techniques, model architectures, and efficiency improvements to propel our science. The Search team sits within Foundations, building agentic search by co-designing model–system interfaces with the core search stack (serving, indexing, retrieval) to translate model intent into reliable, real-world actions. Operating at the frontier of AI and information retrieval, the team develops large-scale systems that transform and index vast corpora, enabling models to reason over global knowledge and act dependably. In close partnership with researchers, we rapidly bring modeling breakthroughs into production and redefine how intelligent systems discover, retrieve, and synthesize information at planetary scale. About the Role We’re looking for a Software Engineer focused on building and scaling retrieval systems. You’ll work with a team of researchers and engineers to develop infrastructure that enables models to retrieve and act on the right information at the right time. This includes designing and operating indexing systems, retrieval pipelines, and serving layers. This work supports retrieval across OpenAI products and research, with direct impact on system performance, reliability, and scale. Responsibilities Build and scale retrieval infrastructure across indexing, serving, and query execution. Develop low-latency, high-throughput systems for real-time model interaction. Partner with research to productionize embedding and retrieval techniques. Support dense, sparse, and hybrid retrieval pipelines. Own system performance, reliability, and observability at scale. Collaborate across Pretraining, Inference, and Product teams to integrate retrieval end-to-e

About the Team The Statsig team within OpenAI builds the experimentation, feature rollout, dynamic configuration, and analytics systems that help OpenAI ship products with speed, safety, and evidence. Our work sits on the critical path for how product, engineering, research, and go-to-market teams learn from real-world usage and make high-confidence decisions. Statsig began as an independent company focused on helping builders move faster through trustworthy experimentation and feature management. After Statsig joined OpenAI, the team began the next chapter: bringing that deep product expertise, customer intuition, and mature platform infrastructure into OpenAI as the experimentation and rollout platform for every product we ship. Today, we support teams across ChatGPT, Codex, model measurement, consumer experiences including ads, business subscriptions, developer products, and the shared infrastructure that connects them. These teams rely on Statsig to safely introduce new capabilities, compare product and model behavior, measure impact, and roll changes forward or back with confidence. We are at a defining moment in the platform journey. OpenAI has the data, product surface area, and pace of innovation to learn faster than almost any organization in the world, but that potential only becomes real if teams can experiment responsibly, measure clearly, and roll out changes safely. Adoption of the platform is accelerating rapidly across the company, and recent SDK and server-side infrastructure work has already produced measurable wins in latency, reliability, memory usage, and compute efficiency for important services. Based out of OpenAI’s Bellevue office, we are a close-knit team that values in-person collaboration, urgency, craft, and impact. We build for other builders, and the best version of this team is one where every OpenAI product team can move faster because the experimentation and rollout layer is dependable, fast, and easy to use. About the Role We are l