Hardware Platform Security Architect Jobs

Who we are About Privy Our mission is to make privacy and user ownership the default online. To do so, we build simple, flexible APIs and tools for developers that make it easy to build new products on crypto rails. Privy owns the abstractions and infrastructure layer above wallets, integrating across chains, third-party providers, and Stripe products like Treasury and Link. We get to solve hard technical problems while leveraging Stripe's distribution to reach customers like Ramp, Klarna, Deel, Kraken, Hyperliquid, and Fomo — powering experiences for both mainstream users and crypto natives. Learn more about Privy: Privy and Stripe: Bringing crypto to everyone About the team Engineering at Privy is distinguished by: High urgency: Shipping very small iterations, very fast, to learn very quickly. Product taste: Our customers are developers, and to build effective products for them requires technical knowledge - you will often be "the PM". Security mindset: A great portion of our product is trust. While we have a dedicated security team, every engineer brings security to their designs from the start. In practice, we use boring technology like Node, React, and AWS so we can focus our engineering energy entirely on pushing the boundaries of Privy's core product, e.g. through hardware enclaves, multi-region low latency APIs, and blockchain abstractions that are accessible to mainstream developers. What you’ll do Manage and architect multi-tenant infrastructure that serves billions of requests every month Design our build and deploy systems across the stack, from SDKs to apps to high-traffic APIs to complex secure enclaves, and more – all for a team that ships daily Drive observability across our product and help keep our systems up and performant in our role in the most critical parts of our customers' stacks Advocate for making the right technical investments at the right time in a company with ever-evolving technical needs Who you are Minimum requirements 8

Who we are About Privy Our mission is to make privacy and user ownership the default online. To do so, we build simple, flexible APIs and tools for developers that make it easy to build new products on crypto rails. Privy owns the abstractions and infrastructure layer above wallets, integrating across chains, third-party providers, and Stripe products like Treasury and Link. We get to solve hard technical problems while leveraging Stripe's distribution to reach customers like Ramp, Klarna, Deel, Kraken, Hyperliquid, and Fomo — powering experiences for both mainstream users and crypto natives. About the team Engineering at Privy is distinguished by High urgency—Shipping very small iterations, very fast, to learn very quickly Product taste—Our customers are developers, and to build effective products for them requires technical knowledge—you will often be "the PM." Security mindset—A great portion of our product is trust. While we have a dedicated security team, every engineer brings security to their designs from the start. In practice, we use boring technology like Node, React, and AWS so we can focus our engineering energy entirely on pushing the boundaries of Privy's core product, e.g. through hardware enclaves, multi-region low latency APIs, and blockchain abstractions that are accessible to mainstream developers. What you’ll do We're looking for an exceptional Forward Deployed Engineer to join our team and be the primary technical owner for building out new capabilities with Privy's most important customers. In this role, you will combine technical expertise with a deep understanding of customer and business objectives to architect, develop, and deploy software features that address customers’ needs and evolve the capabilities of Privy’s core products. Customer obsession is a core part of Privy’s culture. You’ll work closely with fellow engineers, product, and business teams to ensure Privy's customers achieve their desired outcomes and are delighted

Who we are About Privy Our mission is to make privacy and user ownership the default online. To do so, we build simple, flexible APIs and tools for developers that make it easy to build new products on crypto rails. Privy owns the abstractions and infrastructure layer above wallets, integrating across chains, third-party providers, and Stripe products like Treasury and Link. We get to solve hard technical problems while leveraging Stripe's distribution to reach customers like Ramp, Klarna, Deel, Kraken, Hyperliquid, and Fomo — powering experiences for both mainstream users and crypto natives. About the team Engineering at Privy is distinguished by: High urgency: Shipping very small iterations, very fast, to learn very quickly. Product taste: Our customers are developers, and to build effective products for them requires technical knowledge - you will often be "the PM". Security mindset: A great portion of our product is trust. While we have a dedicated security team, every engineer brings security to their designs from the start. In practice, we use boring technology like Node, React, and AWS so we can focus our engineering energy entirely on pushing the boundaries of Privy's core product, e.g. through hardware enclaves, multi-region low latency APIs, and blockchain abstractions that are accessible to mainstream developers. What you’ll do As an Engineering Manager at Privy, you will lead, grow, and shape high-performing engineering teams that make a massive impact on our product and industry. Your North Star is to enable and drive towards the success of Privy’s business overall. The buck stops with you: you are the owner of your team’s ultimate impact on Privy’s product and business. We believe that excellence in management is why our team loves working at Privy. Incredible managers are the core driver behind Privy’s long-term success: they are force multipliers, performance coaches, culture-carriers. They build the scaffolding that supports the team and

Who we are About Privy Our mission is to make privacy and user ownership the default online. To do so, we build simple, flexible APIs and tools for developers that make it easy to build new products on crypto rails. Privy owns the abstractions and infrastructure layer above wallets, integrating across chains, third-party providers, and Stripe products like Treasury and Link. We get to solve hard technical problems while leveraging Stripe's distribution to reach customers like Ramp, Klarna, Deel, Kraken, Hyperliquid, and Fomo — powering experiences for both mainstream users and crypto natives. About the team Engineering at Privy is distinguished by: High urgency—Shipping very small iterations, very fast, to learn very quickly. Product taste—Our customers are developers, and to build effective products for them requires technical knowledge —you will often be "the PM". Security mindset—A great portion of our product is trust. While we have a dedicated security team, every engineer brings security to their designs from the start. In practice, we use boring technology like Node, React, and AWS so we can focus our engineering energy entirely on pushing the boundaries of Privy's core product, e.g. through hardware enclaves, multi-region low-latency APIs, and blockchain abstractions that are accessible to mainstream developers. At Privy, our Forward Deployed Engineers work on the company’s most important customer problems. They partner closely with customers to architect our most complex integrations and build new product features that close the gap to win deals. What you’ll do We’re looking for an Engineering Manager to lead this team as it continues to grow. You’ll be responsible for helping an outstanding group of Forward Deployed Engineers do the best work of their careers while staying laser-focused on helping Privy and its customers win. This is a high-leverage role at the intersection of customers, product development, and engineering. You’ll help the team stay

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Position Overview: As a Staff/Principal Equipment Engineer within PROCT ADT, you will provide technical leadership to improve equipment performance, capability, and global manufacturing outcomes. You will lead complex, multi-site initiatives to resolve equipment challenges, enable technology node readiness, and drive yield and defectivity improvements. This role requires deep expertise, strong ownership, and the ability to influence across teams and suppliers to deliver measurable impact in cost, performance, and scalability. Responsibilities Lead global ownership of equipment performance across toolsets, driving improvements in stability, availability, matching, and efficiency. Direct complex, multi-fab root cause analysis for equipment-driven yield, defectivity, and reliability issues using data-driven and physics-based approaches. Provide technical leadership in tool hardware and chamber behavior to expand process capability and improve performance limits. Partner with Technology Development, integration, and process teams to enable node readiness, volume ramp, and disciplined change control. Influence equipment supplier strategy by leading technical engagements, driving design improvements, and aligning roadmaps to business needs. Drive global standardization through development, validation, and deployment of Best Known Methods (BKMs) across sites. Lead initiatives to improve cost of ownership, reduce variation,

About the Team OpenAI’s Legal team plays a crucial role in advancing our mission by tackling innovative and fundamental legal issues in AI. The team includes professionals from diverse legal fields—technology, AI, infrastructure, privacy, IP, corporate, employment, tax, regulatory, and litigation—who collaborate closely with colleagues across the company. If you are passionate about being a technology lawyer working on cutting-edge challenges, you’ll thrive here. About the Role We’re seeking a senior lawyer to participate in commercial legal strategy and execution across OpenAI’s fast-growing infrastructure portfolio. This is a cross-functional role that will partner closely with procurement, supply chain, partnerships, finance, and product teams to structure, negotiate, and manage the transactions that will support OpenAI’s long-term infrastructure ambitions. We’re looking for an experienced infrastructure transactions lawyer who thrives in ambiguity and wants to help define the commercial playbook for infrastructure efforts in the AI era. This role reports to the Associate General Counsel for infrastructure. 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 commercial legal strategy and risk management for OpenAI infrastructure transactions. Draft, negotiate, and advise on complex agreements with infrastructure suppliers, manufacturers, distributors, and technology partners. Support strategic partnerships involving AI infrastructure and hardware supply chains. Develop frameworks for procurement, licensing, and collaboration across the infrastructure ecosystem. Partner with finance and operations teams to align contract terms with business and compliance requirements. Collaborate with policy and regulatory colleagues on issues impacting global supply chains, export controls, and manufacturing. Build scalable, efficient contracting process

About the Team The Post-Training Frontiers team is responsible for training the frontier agents OpenAI ships to the world (GPT-Next). We train the flagship agentic models behind Codex, ChatGPT, and the API through large-scale reinforcement learning. The team’s work spans four areas. First, execution and science: working with teams across OpenAI to decide what can go into the final model and how, using scientific experiments and evals that are representative of the final pipeline so issues can be recognized early. Second, RL scaling: executing the final large-scale reinforcement learning run, making sure GPUs are used efficiently and training stays healthy. Third, research: improving horizontal capabilities like instruction following, factuality, memory, and multi-agent behavior, where the team’s broad visibility helps identify cross-cutting improvements across teams and domains. Fourth, engineering: maintaining the infrastructure stack and internal tools to ensure that both the final run and all integrations go as smoothly as possible and that the systems are easy to work with. About the Role This role focuses on keeping our frontier RL training runs fast, reliable, and unblocked. You will work across engineering and infrastructure problems as they emerge, from scaling and orchestration issues to inference bottlenecks, numerical problems, and hardware failures, as well as supporting large horizontal integrations in the big run, like multi-agent capabilities or memory. This is a role for a strong generalist who quickly learns anything needed for the task, has high attention to detail, debugs deeply, and is motivated by fixing the highest-impact problem in front of the team. In this role, you will: Keep large-scale async RL training runs moving by jumping into the most urgent engineering and infrastructure problems. Debug issues across training systems, inference, orchestration, scaling, and distributed infrastructure. Improve the reliability and efficiency of RL trai

About the Team The Frontier Systems team at OpenAI builds, launches, and supports the largest supercomputers in the world that OpenAI uses for its most cutting edge model training. We take data center designs, turn them into real, working systems and build any software needed for running large-scale frontier model trainings. Our mission is to bring up, stabilize and keep these hyperscale supercomputers reliable and efficient during the training of the frontier models. About the Role As a Software Engineer on the Frontier Systems team focused on power management, you will work on critical infrastructure to support cutting-edge research. With large-scale supercomputers consuming substantial amounts of power, managing this efficiently is key to maximizing computational capacity. This role is critical to ensuring that our cutting-edge research supercomputing infrastructure runs smoothly, while maintaining reliability and grid-level power stability. Our team empowers strong engineers with a high degree of autonomy and ownership, as well as ability to effect change. This role will require a keen focus on system-level comprehensive investigations and the development of automated solutions. We want people who go deep on problems, investigate as thoroughly as possible, and build automation for detection and remediation at scale. In this role, you will: Develop and implement system-level and software-level solutions to optimize power usage in large-scale supercomputers, ensuring efficient and reliable operations. Build automation to monitor power consumption patterns during training workloads and design algorithms to stabilize these fluctuations, preventing issues with grid reliability. Work with researchers and engineers to design tools for real-time monitoring, detection, and remediation of power-related hardware and system faults. Collaborate cross-functionally to translate complex electrical system requirements into code, while driving continuous improvements in power man

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 The Core Network Engineering team owns the end-to-end networking stack that connects OpenAI’s compute infrastructure — spanning global WAN/edge connectivity, data-center networking, and high-performance host/xPU networking used for large-scale training and inference workloads. This team is responsible for ensuring networking is never the bottleneck to model training efficiency, cluster reliability, or fleet expansion. They design and operate the systems that provide predictable, high-throughput, low-latency connectivity across some of the world’s most advanced AI infrastructure. About the Role We’re looking for engineers to help build and operate the networking foundation behind OpenAI’s frontier AI systems. Depending on your background and area of focus, you may work across host networking, datacenter fabrics, or global WAN infrastructure. The problems span low-level systems software, distributed infrastructure, protocol readiness, observability, performance engineering, automation, and large-scale network operations. You’ll work on systems where microseconds of latency, tail performance, and network reliability directly impact model training efficiency and production serving performance. This role is ideal for engineers who enjoy operating close to the hardware/software boundary and solving performance-critical infrastructure problems at massive scale. In this role, you will: Design, build, and operate networking systems that support large-scale AI training and inference infrastructure Improve performance, reliability, and scalability across host networking, datacenter fabrics, and WAN systems Develop automation for provisioning, configuration management, validation, upgrades, and lifecycle management of networking infrastructure Build tooling and observability systems for network health, performance analysis, debugging, and automated remediation Optimize network performance across technologies such as RDMA, RoCE, InfiniBand, Ethernet, and high-perf

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but are operational in how we do our work, and are committed to supporting all products and research at OpenAI. Our Security team tenets include: prioritizing for impact, enabling researchers, preparing for future transformative technologies, and engaging a robust security culture. About the Role OpenAI is seeking a Security Engineer to join our Infrastructure Security (InfraSec) team. InfraSec protects the foundations of OpenAI’s research and production environments, spanning GPU supercomputing clusters, multi-cloud infrastructure, datacenters, networking, storage, and the critical services that power our frontier AI models. Our charter includes securing everything from bare-metal hardware and firmware, to Kubernetes clusters and service meshes, to data storage and access pathways for highly sensitive model weights and user data. In this role, you will: Design and build security controls across diverse layers (e.g., physical hardware, firmware/BMC, OS, Kubernetes, networks, and CI/CD) to defend against sophisticated adversaries and insider threats. Collaborate with engineering and security teams to drive deployment of security enhancements and control changes across broad-scale infrastructure. Tackle high-impact projects such as checkpoint encryption, network isolation, secret management, and machine identity, while continuously raising the security bar for emerging AI workloads. Take a generalist approach to building security controls, balancing a mix of security expertise and broad technical skillsets to adapt to evolving challenges. You will thrive in this role if you have: Deep understanding of security principles, best practices, and common vulnerabilities. A proactive mindset, with the ability to identify and address secu

About the Team OpenAI is building the infrastructure foundation for the next generation of AI. The Data Center Engineering team defines the strategy, reference architectures, technical requirements, and delivery standards for the large-scale data centers that support OpenAI research, products, and infrastructure partners. As a Data Center Infrastructure Electrical Engineer, you will help define, validate, and scale the electrical power systems that support high-density AI compute. You will translate evolving compute requirements into practical facility and rack-power architectures, evaluate new technologies and vendor solutions, and drive technical decisions across design, manufacturing validation, construction, commissioning, deployment, and operations. This role is best suited for a senior hands-on engineer with deep experience in mission-critical power systems, strong judgment under ambiguity, and the ability to connect facility infrastructure, hardware requirements, controls, telemetry, reliability, and operations. About the Role We are seeking a senior electrical infrastructure engineer to lead the development of reliable, scalable, and efficient power architectures for high-density, liquid-cooled AI data centers. The ideal candidate has strong practical experience with critical electrical systems at data centers or comparable industrial scale, including medium-voltage and low-voltage distribution, utility interfaces, backup power, UPS and battery systems, rack power delivery, grounding, protection, controls, and monitoring systems. You should be comfortable moving between long-range architecture, detailed engineering review, lab validation, vendor qualification, field deployment, and operational troubleshooting. Key Responsibilities Design and optimize electrical topologies and equipment strategies that reduce cost, accelerate schedules, improve efficiency, increase scalability, and maintain high reliability and maintainability. Review and develop basis-of-des

About the Team The Release Engineer team is responsible for building and maintaining the systems that power software delivery—from CI/CD pipelines and artifact management to release automation and fleet telemetry. We ensure software across bootloaders, firmware, operating systems, and cloud services is built reproducibly, validated rigorously, and released safely at scale. About the Role As a Release Engineer, you’ll design, build, and operate release infrastructure that enables reliable, secure, and traceable software delivery across complex multi-component systems. You’ll partner closely with embedded, cloud, and QA teams to ensure that every build—from development to OTA deployment—is fast, verifiable, and production-ready. We’re looking for engineers who take pride in automation, build reproducibility, and system reliability—and who enjoy building the connective tissue that allows hardware and software to ship together seamlessly. This role is based in San Francisco, CA. We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees. In this role, you will: Design and operate CI/CD pipelines for multi-component builds (bootloader, firmware, OS images, backend, companion apps) using hermetic toolchains. Define versioning and branching strategies; automate promotions, changelogs, and artifact retention. Integrate unit, integration, and hardware-in-the-loop (HIL) test results; quarantine flaky tests, auto-bisect failures, and block unsafe promotions. Build A/B OTA update flows with verity and health checks; run staged rollouts and canaries; implement safe rollback and roll-forward strategies. Implement code signing for binaries and firmware, generate SBOMs, run vulnerability scanning, and attach build attestations and provenance. Manage dashboards and alerts for build health, promotion latency, failure rates, and fleet update telemetry. You might thrive in this role if you: Have experience building and operating buil

About the Team Our team analyzes inference stack performance across the application, model, and fleet layers to identify bottlenecks and drive faster, cheaper inference. We combine systems profiling, benchmarking, and analysis to understand where time and cost are spent, then turn that understanding into performance optimizations and models that project performance and capacity needs for future launches. About the Role In this role, you will model inference performance across application, model, and fleet layers with higher fidelity. You will build cost-to-serve estimates from microbenchmarks and create tools that help cross-functional teams reason about latency, capacity, utilization, and cost tradeoffs. In this role, you will Build and refine performance models that translate microbenchmark results into cost-to-serve estimates. Analyze inference workloads end to end across applications, models, and fleet infrastructure. Enhance tooling to identify bottlenecks across layers for latency and throughput. Partner with other teams to turn performance insights into concrete improvements and project how future changes affect inference. You might thrive in this role if you: Enjoy reasoning from first principles about distributed systems, model inference, and hardware efficiency. Are comfortable working across abstraction layers, from application behavior to kernels, accelerators, networking, and fleet scheduling. Have deep expertise with performance profiling, benchmarking, analysis, and optimization. Enjoy collaborating with engineering and research teams to improve real production systems. 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 systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve o

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but are operational in how we do our work, and are committed to supporting all products and research at OpenAI. Our Security team tenets include: prioritizing for impact, enabling researchers, preparing for future transformative technologies, and engaging a robust security culture. About the Role OpenAI is seeking a Principal Security Engineer to join our Infrastructure Security (InfraSec) team. InfraSec protects the foundations of OpenAI’s research and production environments, spanning GPU supercomputing clusters, multi-cloud infrastructure, datacenters, networking, storage, and the critical services that power our frontier AI models. Our charter includes securing everything from bare-metal hardware and firmware, to Kubernetes clusters and service meshes, to data storage and access pathways for highly sensitive model weights and user data. As a principal engineer, you will set technical direction and drive execution on high-impact infrastructure security programs, partnering across various orgs at OpenAI to deliver durable controls that raise the security bar at OpenAI scale. In this role, you will: Own end-to-end security outcomes for one or more critical infrastructure areas, including multi-quarter strategy, roadmap, and delivery. Design and build security controls across diverse layers (e.g., physical hardware, firmware/BMC, OS, Kubernetes, networks, and CI/CD) to defend against sophisticated adversaries and insider threats. Lead cross-functional programs to deploy security enhancements and control changes across broad-scale infrastructure, balancing security guarantees with reliability and velocity. Take a generalist approach to building security controls, balancing a mix of security expertise and broad technical skillsets