System Engineer Cloudflare Hyperdrive Salary India in San Francisco

About the Team OpenAI’s Forward Deployed Engineering team partners with leading semiconductor companies to deploy production-grade AI systems across the entire chip design lifecycle: design, verification, and physical design. We operate at the intersection of customer delivery and core platform development, embedding deeply with customers to translate frontier model capabilities into systems that materially improve engineering workflows and accelerate innovation. Our work turns early, high-touch deployments into repeatable solution patterns, reference architectures, and evaluation practices that scale across the semiconductor ecosystem. About the Role We are seeking a highly skilled Physical Design Engineer to join our semiconductor-focused Forward Deployed Engineering team. This is a senior IC role that will begin with a strong emphasis on physical design expertise, technical judgment, advisory leverage, and customer credibility, with the expectation that the person will grow into a broader Forward Deployed Engineering role over time. In the near term, you will serve as the team’s physical design SME across semiconductor deployments: helping FDEs, Product, and Research understand backend implementation workflows, pressure-test AI-assisted solution ideas against real physical design constraints, and raise the quality of our customer-facing technical work. You will help the broader team build fluency in implementation flows, EDA tooling, signoff methodology, and the trade-offs that shape physical design decisions in practice. Over time, we expect this role to expand beyond SME support into broader FDE ownership: partnering directly with customers, shaping deployment strategy, building and iterating production-grade AI systems, driving technical workstreams, and helping turn high-touch semiconductor deployments into repeatable solutions. This is a strong fit for someone who brings deep physical design expertise today and is excited to grow into a customer-facing, syst

About the Team OpenAI develops models that can reason through complex problems and hardware designed for the demands of advanced AI. AI for Chips connects these efforts: applying increasingly capable AI systems to the work of semiconductor engineering. Our goal is to help engineers develop better chips and shorten design cycles. This work brings research, model training, and hardware expertise together to build tools that engineers can use on real designs, with correctness and measurable performance at the center. About the Role We’re hiring a Software Engineer to build the research infrastructure and tooling that help OpenAI models design silicon. You’ll turn chip-design workflows into reliable environments for reinforcement learning and evaluation, and make it easier for researchers to run experiments and iterate on new ideas. You’ll move between software engineering, tool integration, and open research problems. We value strong coding fundamentals, clear technical judgment, and independent execution. Prior chip-design experience is helpful, but you can learn the domain alongside the team’s hardware specialists. In this role, you will: Build and maintain infrastructure for reinforcement learning environments, evaluations, and long-running experiments. Integrate electronic design automation (EDA) tools into workflows for RTL generation, verification, and physical design optimization. Improve experiment reliability, reproducibility, observability, and performance; debug failures across tools, services, and infrastructure. Develop tooling and model harnesses that let researchers test ideas quickly and measure correctness and power, performance, and area (PPA). Collaborate with researchers and engineers to turn successful experiments into reusable systems and training workflows. Own ambiguous projects end to end, communicate progress, and use results to guide the next iteration. You might thrive in this role if you: Have strong software engineering fundamentals, with

We are hiring a Security Software Engineer to design and implement the hardware-backed security foundations used across OpenAI’s device ecosystem. A central focus of this role is hardening the boundary between our policy systems and the HSMs that protect sensitive cryptographic keys. This boundary determines which operations may be performed, what may be signed, which policies must be satisfied, and how changes to trusted software and policy are authorized. You will develop security-critical software and firmware within, or immediately adjacent to, an HSM trust boundary. Depending on your background, this may include HSM trusted applications, firmware services, cryptographic mechanisms, device drivers, PKCS#11 components, secure-provisioning protocols, or signing-policy enforcement systems. This is a hands-on software-engineering role. You will be expected to design systems, write and review production code, debug across hardware and software boundaries, and carry projects from initial requirements through deployment. It is not an HSM administration, PKI operations, compliance, or architecture-only position. In This Role, You Will Design and implement security-critical software and firmware for HSMs, secure elements, trusted execution environments, and hardware roots of trust. Build and harden the policy-to-HSM boundary responsible for authorizing certificate issuance and cryptographic signing operations. Develop HSM trusted applications, firmware components, host interfaces, device drivers, SDKs, or cryptographic service integrations. Implement or extend cryptographic interfaces such as PKCS#11, OpenSSL providers or engines, platform key-storage APIs, or comparable hardware-security interfaces. Build firmware and software that cryptographically enforces key generation, provisioning, usage, rotation, recovery, and destruction policies. Design and implement HSM-backed certificate authority, code-signing, key-management, and device-identity systems. Develop end-to-end

Drata is building the trust layer between great companies - automating compliance, managing risk, and helping organizations prove trust continuously as they scale. We're Dratanauts: a global crew of 600+ professionals united by a culture that rewards integrity, ownership, and raising the bar, no matter where in the world we're working from. Why Join the Drata Team? At Drata, you're not maintaining legacy compliance software - you're building the agentic AI platform defining what trust looks like for the next generation of companies. Here's what makes the work itself worth showing up for: Problems without a playbook: You'll work at the edge of AI and security, building agentic governance, continuous compliance, and real-time trust verification to solve problems that don't have an established answer yet. You're writing it as you go. Real ownership, not just process: Our values center on owning outcomes and raising the bar, not checking boxes. You're expected to have opinions and back them. A seat at the table: Your perspective is unique and valued. Open debate and diverse viewpoints are built into how decisions actually get made here, at every level. Growth at rocketship speed: Drata is scaling fast, which means scope grows fast too. High performers get more ownership, visibility, and experience. A crew, not just coworkers: Dratanauts consistently describe a "come as you are" culture with sharp, curious people—the kind of team that makes hard problems genuinely fun to solve. See what they say here and follow us on LinkedIn for company news, employee stories, and career updates. Job Summary: The Software Engineer, Monetization Platform serves as an engineer on the Product Platform Group with a primary focus on the systems that turn product usage, subscriptions, credits, commitments, and contracts into accurate customer outcomes and clean financial operations. This person will help architect and evolve the core billing domain for Drata: usage event ingestion, billable m

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the Role At Sentry, Support is an engineering discipline. Our customers are the greatest technical minds in the world—developers at elite enterprises building the future of software—and they deserve answers that go deeper than a knowledge base link. We're looking for an APAC Technical Support Engineer based in San Francisco to join our global Support Engineering team. This role is designed to provide APAC coverage to our users; with the shift being Sunday through Thursday 4PM-12AM PST. We are architecting the Technical Support engine . We’re looking for an experienced engineer to help us redefine the standard of technical support by combining deep human expertise with autonomous agentic systems. You are a debugger of both code and systems. You will treat support volume as a data signal to build automated resolution paths, ensuring our human engineers only touch the most complex, high-impact architectural puzzles. Sentry Support Engineers aren't just clearing queues; they are Orchestrators . You will engage with our users across GitHub, Discord, and our internal systems, while acting as the Technical Lead for our Agentic Ops. You ensure that when a developer asks a complex question, our systems have the right context and a seamless "Human-in-the-Loop" path to you when deep, nuanced expertise is required. In this role you will Master the Sentry Ecosystem & Support Elite Developers Deep-Dive Debugging: Perform root-cause analysis on complex issues and distributed tracing gaps across polyglot environments. Support the Great Minds: Act as a strategic consultant for senior engineers at our largest enterprise customers, s

About the Team API Agents builds the shared agent harness, tools, and infrastructure that turn OpenAI’s frontier models into systems that can reliably complete real work. We carry the capabilities behind Codex into a much broader set of products and workflows across software engineering, research, finance, healthcare, enterprise operations, and more. Our work spans search and connected context, computer use, memory, delegation and multi-agent coordination, and safe execution. Sitting at the intersection of Research, Codex, infrastructure, and applied product teams, we build reusable agent capabilities that compound across the ecosystem. About the Role We are looking for an experienced backend software engineer to build the core systems behind the next generation of agents. You will design reliable services and abstractions that help agents find the right context, use tools and computers, retain knowledge, coordinate over long-running workflows, and take action safely. The role combines deep backend and infrastructure work with strong product judgment, with opportunities to work across agent runtimes, orchestration, search, execution environments, identity and permissions, observability, and evaluations. This is software and systems engineering rather than model training: success comes from strong backend fundamentals, high agency, and the ability to turn fast-moving research capabilities into dependable production primitives. In this role, you will: Design, build, and operate the shared agent harness and backend infrastructure that power long-running, high-value workflows across OpenAI and third-party products. Build reusable capabilities across search and connected context, computer use, memory, tool execution, delegation, subagents, and multi-agent orchestration. Establish the foundations agents need to operate safely in production, including secure execution environments, identity and permissions, observability, evaluations, reliability, and cost and latency effi

About the Team The Monetization team is a 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 build measurement systems that connect ad interactions to meaningful advertiser outcomes while protecting user privacy. In this foundational role, you’ll design infrastructure for conversion signals, attribution, reporting, and feedback loops across OpenAI’s ads products. This role is ideal for engineers who have built large-scale ads measurement, data, experimentation, marketplace, or distributed systems and want to apply that experience in a highly ambiguous 0→1 environment. You’ll work across event collection and normalization, deduplication and matching, attribution and modeled measurement, privacy-safe aggregation, reporting, and high-quality labels for ads optimization. We are hiring engineers who can independently own complex systems, make sound technical tradeoffs, and help define what should be built. You’ll work closely with Ads Delivery, Ads ML, Product, Research, Privacy, Data Sc

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 machine learning infrastructure that powers OpenAI’s monetization and ads systems. In this foundational role, you’ll design and develop the platform layer that enables teams to build, train, deploy, serve, monitor, and continuously improve machine learning models used across advertising and monetization products. You’ll work across the full ML lifecycle, from large-scale data pipelines and feature infrastructure to training systems, model serving, experimentation platforms, and monitoring frameworks. The systems you build will support high-throughput, low-latency advertising workloads while maintaining strict standards for reliability, privacy, security, and performance. This role sits at the intersection of machine learning systems, distributed infrastructure, and monetization, offering the opportunity to shape the core platforms that help translate model innovation into m

About the Team We’re hiring a Developer Productivity engineer to support OpenAI’s Inference Runtime teams. These teams own the systems responsible for serving models reliably, efficiently, and safely across Codex, ChatGPT, API, and internal research workloads. We’re hiring a Developer Productivity Engineer to help scale the engineering systems, safeguards, and developer workflows that enable our teams to move quickly without compromising reliability or performance. This role sits at the intersection of developer experience, CI/CD infrastructure, release engineering, production readiness, and inference systems reliability. You’ll work on the tooling and operational foundations that support model launches, inference optimizations, cloud provider integrations, and large-scale deployments across a rapidly evolving inference stack. About the Role We’re looking for an autonomous, high-ownership engineer who cares deeply about making other engineers faster, safer, and more confident. A major focus of this role will be improving the tooling and infrastructure around deploy gates for inference engine images. These systems help ensure that every image released to production and research is correct, numerically sound, free of regressions, and performant across key metrics like time-to-first-token (TTFT) and time-between-tokens (TBT). You’ll help harden the systems that catch issues before they reach production, reduce noise from flaky or infrastructure-related test failures, and improve automation around triage, ownership, debugging, and escalation when failures occur. You’ll also work on improving observability, rollout safety, release automation, and developer self-service tooling across a rapidly evolving inference stack. This is not generic internal tools work. The systems you build directly impact OpenAI’s ability to support new model launches, safely ship inference optimizations to the world, onboard new infrastructure providers, and operate one of the largest and most p

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, advertisers, 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 new ad experiences into real-world systems across OpenAI surfaces at global scale, including thoughtfully integrating them into the core ChatGPT experience. About the Role We’re looking for an experienced Software Engineer to help build the creative rendering and presentation layer of OpenAI’s ads ecosystem. This is a foundational role responsible for defining how ads are structured, rendered, and delivered across different surfaces, platforms, and media types. You’ll work across the full technical stack to build infrastructure and tooling for new ad formats, including text, image, video, native, conversational, and interactive experiences. You will help ensure these formats render reliably, perform efficiently, and feel natural within the core ChatGPT experience. You’ll collaborate deeply with Product, Design, and Research to create ads experiences that are useful, high-quality, privacy-preserving, and aligned with OpenAI’s standards for safety and user trust. In this role, you will: Design, build, and

About the Team The Storage Infrastructure team builds and operates the storage foundation behind OpenAI’s most demanding workloads. We work directly with research to design storage systems for rapidly evolving experiments, while also powering production at scale. We own the platform end to end: backend systems, user-facing services and APIs, and the control planes that manage how data is placed, moved, and retained over time. Our stack spans cloud and in-house object stores across very different workload profiles, from GPU-attached systems to dedicated storage hardware. We also build the federation layer that unifies these backends behind a simple interface and routes each workload to the right storage solution. About the Role You will help build the storage platform that powers OpenAI’s research and production systems. This is a hands-on infrastructure role for engineers who want to work on deeply technical systems at scale and own them in production. You’ll work across object storage, cross-region data movement, lifecycle management, and the federation layer that provides a unified interface across multiple backends. Much of our stack runs on Kubernetes, and we primarily build services in Rust. In this role, you will: Build and operate storage services that underpin OpenAI’s research infrastructure Develop object storage systems across cloud and in-house environments Build systems for cross-region data movement, replication, and recovery Design lifecycle management capabilities that keep data durable, available, and cost-effective Evolve the federation layer that unifies multiple backend systems behind a simple interface Improve performance, reliability, and operational excellence across the platform Collaborate closely with researchers and infrastructure teams to support rapidly evolving workloads You might thrive in this role if you: Have experience building or operating distributed systems in production Have worked on storage infrastructure, object stores, dist

About the Team The Workload team is responsible for designing and running OpenAI’s LLM training and inference infrastructure that powers frontier models at massive scale. Our systems unify how researchers train and serve models, abstracting away the complexity of performance, parallelism, and execution across vast GPU/accelerator fleets. By providing this foundation, the Workload team ensures that researchers can focus on advancing model capabilities while we handle the scale, efficiency, and reliability required to bring those models to life. About the Role We are looking for an engineer to design and implement the dataset infrastructure that powers OpenAI’s next-generation training stack. You will be responsible for building standardized dataset interfaces, scaling pipelines across thousands of GPUs, and proactively testing performance bottlenecks. In this role, you will collaborate closely with the multimodal researchers, and other infra groups to ensure datasets are unified, efficient, and easy to consume. In this role, you will: Design and maintain standardized dataset APIs, including for multimodal (MM) data that cannot fit in memory. Build proactive testing and scale validation pipelines for dataset loading at GPU scale. Collaborate with teammates to integrate datasets seamlessly into training and inference pipelines, ensuring smooth adoption and a great user experience. Document and maintain dataset interfaces so they are discoverable, consistent, and easy for other teams to adopt. Establish safeguards and validation systems to ensure datasets remain reproducible and unchanged once standardized. Debug and resolve performance bottlenecks in distributed dataset loading (e.g., straggler systems slowing global training). Provide visualization and inspection tools to surface errors, bugs, or bottlenecks in datasets. You might thrive in this role if you: Have strong engineering fundamentals with experience in distributed systems, data pipelines, or infrastructure.

About the Team The Privacy Engineering Team at OpenAI is committed to integrating privacy as a foundational element in OpenAI's mission of advancing Artificial General Intelligence (AGI). Our focus is on all OpenAI products and systems handling user data, striving to uphold the highest standards of data privacy and security. We build essential production services, develop novel privacy-preserving techniques, and equip cross-functional engineering and research partners with the necessary tools to ensure responsible data use. Our approach to prioritizing responsible data use is integral to OpenAI's mission of safely introducing AGI that offers widespread benefits. About the Role As a part of the Privacy Engineering Team, you will work on the frontlines of safeguarding user data while ensuring the usability and efficiency of our AI systems. You will help us understand and implement the latest research in privacy-enhancing technologies such as differential privacy, federated learning, and data memorization. Moreover, you will focus on investigating the interaction between privacy and machine learning, developing innovative techniques to improve data anonymization, and preventing model inversion and membership inference attacks. This position is located in San Francisco. Relocation assistance is available. In this role, you will: Design and prototype privacy-preserving machine-learning algorithms (e.g., differential privacy, secure aggregation, federated learning) that can be deployed at OpenAI scale. Measure and strengthen model robustness against privacy attacks such as membership inference, model inversion, and data memorization leaks—balancing utility with provable guarantees. Develop internal libraries, evaluation suites, and documentation that make cutting-edge privacy techniques accessible to engineering and research teams. Lead deep-dive investigations into the privacy–performance trade-offs of large models, publishing insights that inform model-training and prod

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 infrastructure behind OpenAI’s monetization and ads systems. In this foundational role, you’ll architect and implement distributed systems that power OpenAI’s monetization stack—focusing on reliability, performance, privacy, and large-scale operation. You’ll work across backend, systems, and platform layers to define and implement 0→1 infrastructure, partnering closely with Product, Design, and Research to shape the future of monetized AI experiences. Your work will enable both internal and external teams to build on safe, scalable, and robust monetization primitives. This role is exclusively based across our San Francisco & Seattles sites. We offer relocation assistance to new employees. In this role, you will: Design and build the foundational backend and infrastructure powering OpenAI’s monetization and ads systems Architect large-scale distributed systems that

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, advertisers, 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 new ad experiences into real-world systems across OpenAI surfaces at global scale, including thoughtfully integrating them into the core ChatGPT experience. About the Role We’re looking for an Android Engineer to help build the native Android experiences and client-side systems that power how ads are structured, rendered, and delivered across OpenAI’s ads ecosystem. This role sits within the Ads Formats team, which owns the creative rendering and presentation layer for next-generation ads experiences across different surfaces and media types. You’ll help build the Android infrastructure and tooling that support formats such as text, image, video, native, conversational, and interactive ads, while ensuring they render reliably and perform efficiently across platforms. You’ll work closely with backend, Product, Design, Research, and Safety partners to shape Android architecture that supports user-first, privacy-preserving monetization experiences within ChatGPT and OpenAI’s broader mobile ecosystem. In th