Infrastructure Sourcing Operations Lead in United States

About Pinecone Pinecone is the knowledge infrastructure for AI at scale. Its leading vector database and knowledge engine, Pinecone Nexus, power accurate, performant AI applications for more than 9,000 customers and 800,000 developers worldwide. Pinecone's mission is to make AI knowledgeable. Pinecone is based in New York and raised $138M in funding from Andreessen Horowitz, ICONIQ, Menlo Ventures, and Wing Venture Capital. About the Team and Role: We are hiring a senior/staff software engineer to help design and build core components of our next-generation knowledge retrieval system built for the AI era – search and retrieval infrastructure that powers high-quality, scalable, and enterprise-grade agentic systems. You’ll build the framework that allows our customers to connect knowledge–synthesized from structured and unstructured data–to modern LLM-powered applications, leveraging the world’s best-in-class vector DB supporting semantic search and hybrid retrieval. This role is ideal for someone who loves backend system architecture, distributed systems, and applied AI infrastructure. It is a high impact role with significant ownership across architecture, performance, and system reliability. Responsibilities: Design and build scalable platform components leveraging advanced retrieval via query planning, semantic and hybrid search, metadata-aware search, and LLM generation Design and build optimized indexing pipelines for structured and unstructured data Build backend services for semantic and hybrid retrieval, knowledge graph construction, and retrieval orchestration Improve retrieval quality through evaluation and observability frameworks Design APIs for internal and external user and agentic consumers Optimize latency, throughput and cost across large-scale inference and retrieval workloads Drive technical direction for reliability and security What You’ll Bring to the Table: To thrive in this role, you don't need to check every single box, but you should be deep

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. As a member of the Infrastructure Foundation Hardware Engineering team, you will play a key role in enabling our mission to deliver a reliable, high-performing, and cost-efficient infrastructure that powers the world’s play. In this specialized role, you will be the technical lead for our GPU and AI accelerator ecosystem. You will be responsible for the full lifecycle of GPU hardware, from initial architectural evaluation and firmware qualification to large-scale fleet integration and performance tuning. You will ensure that Roblox’s massive-scale rendering and ML workloads run on the most optimized and stable hardware possible. You Will: Architect & Prototype: Prototype next-generation GPU-accelerated hardware platforms, ensuring seamless integration between high-density compute nodes, high-speed interconnects (NVLink/PCIe Gen5/6), and system firmware. GPU Optimization: Drive the integration, performance testing, and debugging of GPUs in our fleet, focusing specifically on hardware-level optimizations, driver tuning, and thermal/power management. Validation & Certification: Develop and execute rigorous evaluation and stress-testing strategies for GPU-heavy server platforms to ensur

About the Team The compute infrastructure team runs the GPU fleet and large-scale compute clusters that serve the models backing ChatGPT and the API, while also supporting training workloads for our next generation models. We operate a large, modern GPU fleet and provide a unified platform for other OpenAI teams to seamlessly run production Applied AI and Research training workloads. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role You will be part of an engineer-first TPM team as a Technical Program Manager for Compute Infrastructure who owns the end-to-end delivery of large-scale GPU clusters, partnering with engineers to bring clusters online across external providers and partners. You’ll run a broad, parallel portfolio spanning hardware, networking, power, and cooling—driving execution, risk management, and crisp alignment from working teams through leadership to deliver production-ready capacity at scale. 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: Lead end-to-end delivery of both New Compute SKUs and large-scale GPU clusters across an external partner ecosystem while supporting capacity planning for training and inference. Ability to contextually drive multi-threaded bring-up programs spanning hardware, networking, power, and cooling—owning plans, dependencies, and critical paths. Interface with chip providers to derisk long-term onboarding to new hardware platforms by working across kernels, comms, hardware, and scheduling engineering teams. Build and operationalize program mechanisms (roadmaps, milestones, risk registers, runbooks) that make delivery predictable at massive scale. Partner with engineering to improve cluster turn-up reliability, repeatability, and automation

About the Team The Agent Infrastructure team at OpenAI is responsible for building systems that enable training and deployment of highly useful AI agents, both internally and for the world. We work hand-in-hand with researchers to design and scale the environment in which agentic models are trained – providing a workspace for AI models to execute code, debug issues, and develop software just as human SWEs do. Our training environment for agentic models operates at an extremely high scale and has the flexibility to emulate any environment in which an agent might work. At the same time, our team builds and maintains OpenAI’s core platform for the deployment and execution of agents in production. Our systems power products such as Codex, Operator, tool use in ChatGPT, and future agentic products. Some of the most challenging technical problems in scaling the capabilities and utility of agents and agentic models lie in the infrastructure layer – and our team is focused on building the research and production systems that enable OpenAI to train the most capable models in the world, and maximize the utility of our agentic products for users around the world. About the Role As a Software Engineer on the Agent Infrastructure team, you will have the opportunity to work closely with both research and product at OpenAI - building and scaling systems to train highly capable agentic models, and building the platform and integrations to launch new agents to hundreds of millions of users worldwide. Your work will consist of both building new capabilities - standing up the infrastructure and integrations needed to train more complex agentic models - and rapidly scaling these new capabilities to some of the largest compute clusters in the world. At the same time, you’ll be instrumental to the launch of agentic products at OpenAI - building, maintaining, and scaling the production platform on which all agents run. We’re looking for people with deep experience building AI infrastructu

This role will support the fleet infrastructure team at OpenAI. The fleet team focuses on running the world’s largest, most reliable, and frictionless GPU fleet to support OpenAI’s general purpose model training and deployment. Work on this team ranges from Maximizing GPUs doing useful work by building user-friendly scheduling and quota systems Running a reliable and low maintenance platform by building push-button automation for kubernetes cluster provisioning and upgrades Supporting research workflows with service frameworks and deployment systems Ensuring fast model startup times though high performance snapshot delivery across blob storage down to hardware caching Much more! About the Role As an engineer within Fleet infrastructure, you will design, write, deploy, and operate infrastructure systems for model deployment and training on one of the world’s largest GPU fleet. The scale is immense, the timelines are tight, and the organization is moving fast; this is an opportunity to shape a critical system in support of OpenAI's mission to advance AI capabilities responsibly. 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: Design, implement and operate components of our compute fleet including job scheduling, cluster management, snapshot delivery, and CI/CD systems. Interface with researchers and product teams to understand workload requirements Collaborate with hardware, infrastructure, and business teams to provide a high utilization and high reliability service You might thrive in this role if you: Have experience with hyperscale compute systems Possess strong programming skills Have experience working in public clouds (especially Azure) Have experience working in Kubernetes Execution focused mentality paired with a rigorous focus on user requirements As a bonus, have an understanding of AI/ML workloads About OpenAI OpenAI is an AI resea

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 operational in how we execute, and we support every product and research effort at OpenAI. Our tenets include prioritizing for impact, enabling researchers and developers, preparing for future transformative technologies, and fostering a strong, collaborative security culture. About the Role OpenAI is seeking a Security Software Engineer to join the Infrastructure Security (InfraSec) team. InfraSec safeguards the core of OpenAI’s research and production environments—GPU supercomputing clusters, multi-cloud infrastructure, datacenters, networking, storage, and the critical services that power our frontier AI models. Our charter spans everything from bare-metal hardware and firmware to Kubernetes clusters, service meshes, and the data pathways that carry highly sensitive model weights and user data. As a Security Software Engineer, you will design and build critical foundational services, such as authentication systems, egress/ingress proxies, access brokers, and key management platforms, that demand high standards of reliability, scalability, and software craftsmanship. These systems form the security backbone of OpenAI’s supercomputing environment and must remain robust under intense scale and adversarial pressure. In this role, you will: Architect and implement production-grade security services (e.g., auth services, access brokers, secure proxies, key-management infrastructure) that provide strong guarantees across hardware, operating systems, Kubernetes, networks, and CI/CD. Partner with infrastructure and research engineers to embed security into high-performance compute clusters, enabling rapid model training and deployment without compromising protection. Develop automation and detection tooling to continuously identif

About the Team The GPT Infrastructure team builds systems that turn advances in model inference and optimization into reliable production capabilities. We enable OpenAI workloads to be qualified and optimized across new accelerator platforms without requiring a one-off port and tuning effort for every hardware target. Our work spans distributed systems, model execution, compilers and runtimes, performance engineering, secure partner integrations, evaluation systems, and developer tooling. We build the infrastructure that makes optimization workflows automated, reproducible, and trustworthy. About the Role We are seeking a software engineer to help build the platform that qualifies and optimizes inference workloads across heterogeneous compute environments. You will develop both OpenAI-hosted services and secure partner-side software for running long-lived optimization workflows. These workflows generate candidate kernels, runtime configurations, and serving-stack changes; compile and execute them on target hardware; verify their correctness; measure their performance; and use the results to guide further optimization. You will work across model architecture, distributed execution, compilers, runtimes, networking, and accelerator systems. A central part of the role is turning research prototypes and one-off hardware bring-up efforts into reliable, reusable infrastructure with clear contracts, reproducible results, strong observability, and well-defined security boundaries. Key Responsibilities Design, build, and operate APIs and control-plane services for long-running workload qualification and optimization campaigns, including scheduling, retries, checkpointing, resource budgets, and observability. Build secure partner-side execution and evaluation software that can compile, run, verify, profile, and benchmark candidate artifacts on accelerator hardware. Integrate model workloads, hardware profiles, compiler toolchains, runtimes, serving engines, and distributed-exe

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 operational in how we execute, and we support every product and research effort at OpenAI. Our tenets include prioritizing for impact, enabling researchers and developers, preparing for future transformative technologies, and fostering a strong, collaborative security culture. About the Role OpenAI is seeking a Principal Software Engineer to join the Infrastructure Security (InfraSec) team. InfraSec safeguards the core of OpenAI’s research and production environments: GPU supercomputing clusters, multi-cloud infrastructure, datacenters, networking, storage, and the critical services that power our frontier AI models. Our charter spans everything from bare-metal hardware and firmware to Kubernetes clusters, service meshes, and the data pathways that carry highly sensitive model weights and user data. As a Principal Software Engineer, you will set technical direction and drive execution of critical foundational services, such as authentication systems, egress/ingress proxies, access brokers, and key management platforms, that demand high standards of reliability, scalability, and software craftsmanship. These systems form the security backbone of OpenAI’s customer and supercomputing environment and must remain robust under intense scale and adversarial pressure. In this role, you will: Own the architecture and roadmap for one or more core security services (e.g., authN/Z, policy enforcement, secure proxies, key management), taking them from design to rollout to long-term operation. Design and implement planet-scale security systems that provide strong guarantees across hardware, operating systems, Kubernetes, networks, and CI/CD: balancing security, reliability, latency, and developer ergonomics. Lead cross-functional launches

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . What We're Looking For: 2–4 years of program or project management experience (or equivalent), ideally touching infrastructure, platform, or cloud environments. Working knowledge of cloud platforms (AWS or similar) — compute, storage, and basic usage/cost concepts. Interest in, and some exposure to, capacity management and infrastructure efficiency (right-sizing, utilization, waste reduction); deep FinOps expertise is not required. Strong organizational and execution skills: able to track a program's moving pieces, follow up, and keep things on schedule. Clear written and verbal communication; comfortable presenting status and asks to engineering partners. Collaborative and coachable — works well with engineers and more senior TPMs, seeks input, and takes feedback well. Experience at a large-scale consumer tech or infrastructure organization is

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 Sentry's Infrastructure Engineering team is what makes operating Sentry simple, safe, and seamless for every other engineering team in the company. They build the internal control platforms, configuration systems, traffic routing, and automation that let product engineers operate services safely at scale without needing deep infrastructure expertise themselves. As the Engineering Manager for Infrastructure Engineering, you'll lead a team of engineers building the tools that power Sentry's growth: internal admin and change management tools, configuration automation, and the routing layer that underlies Sentry's architecture. You'll be responsible for technical vision, team health, system reliability, and partnership with engineering teams across the company who depend on your team's tools every day. You'll work closely with leaders across Infrastructure, Platform, and Production Engineering to shape how Sentry scales its operational model as the company grows. In this role you will Lead a team of engineers building the internal control platforms that every engineering team at Sentry relies on to operate services safely. Drive the evolution of Infrastructure Engineering's platform, including configuration management, traffic routing and environment controls Own the team's technical direction, contributing to key decisions on API architecture, internal tooling design, and automation frameworks. Nurture and grow engineers at different levels, providing support through coaching, mentorship, and career development. Foster an inclusive, high-performing team culture focused on ownership, learning, and delivery. Partne

Our work at NVIDIA is dedicated towards a computing model focused on visual and AI computing. For two decades, NVIDIA has pioneered visual computing, the art and science of computer graphics, with our invention of the GPU. The GPU has also shown to be spectacularly effective at solving some of the most complex problems in computer science. Today, NVIDIA’s GPU simulates human intelligence, running deep learning algorithms and acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. We are looking to grow our company and teams with the smartest people in the world and there has never been a more exciting time to join our team! The AI Infrastructure Product Design team creates software used by engineers and researchers to prepare data, run complex workflows, and understand results. This internship offers ownership of a defined product problem from early research through a tested design and implementation handoff. Designers on this team often move between Figma and working HTML prototypes, and may hand off HTML directly to engineering. This work calls for a high standard of visual and interaction design alongside technical fluency. The role is a good fit for someone who enjoys making technically complex systems easier to understand and who uses large language models and software agents thoughtfully as part of their design and prototyping process. What you will be doing: Own a focused design project for an internal AI infrastructure product, from understanding the problem through a validated design and implementation handoff. Interview engineers and researchers, map their workflows, and turn the findings into clear product requirements, user flows, and interaction models. Create precise, implementation-ready interface designs and interactive prototypes in Figma and HTML/CSS, with careful attention to typography, hierarchy, spacing, visual consistency, interactio

NVIDIA is seeking a Senior System Architect: Heterogeneous EDA Systems to solve a complex challenge in accelerated computing: Failure Attribution at Scale. As EDA or equivalent experience workloads scale across thousands of heterogeneous nodes, a single failure can cause massive resource waste. We need an engineer to develop and build an automated framework. This framework will ingest telemetry from CPU and GPU clusters to identify the root cause of job failures in real-time. It will distinguish between hardware faults, infrastructure instability, and software defects. What you'll be doing: Architect Failure Attribution Frameworks: Build a scalable "flight recorder" for EDA jobs that captures high-fidelity state across the CPU, GPU, and Fabric at the moment of failure. Build automated diagnostics that correlate GPU XID errors, PCIe bus failures, and CUDA memory exceptions. Connect these errors with system-level events such as OOM kills or NUMA-related hangs. Distributed Logging & Tracing: Implement low-overhead tracing mechanisms (using tracing tools or custom agents) that provide access to job execution across multi-node Slurm or Kubernetes clusters. Root Cause Automation: Develop heuristics and models based on machine learning to classify failures as "Hardware Fault," "Software Bug," or "Environment Issue." This reduces the Mean Time to Identify (MTTI) for R&D teams. Resiliency Engineering: Work closely with hardware and infrastructure teams to define "signals of impending failure," enabling proactive job migration or check-pointing before a crash occurs. What we need to see: Distributed Systems Mastery: BS, MS, or PhD in Computer Science or Electrical Engineering (or equivalent experience) with 6+ years in systems programming. Experience building automated

About VSCO For years, we've helped photographers create their work. Now we're building what comes next. VSCO exists for photographers. Not as a side feature, not as an afterthought, but as the whole point. We build the connected system photographers rely on, and we've spent over a decade earning the trust of a global creative community that takes the craft seriously. Photography is at an inflection point. AI is reshaping what's possible for creative work, and that's where our mission shines. VSCO is building the full photographer's workflow: from creating and editing your work, to delivering it to clients, to running your business. All of it built thoughtfully, with photographers leading the way. We believe the future of photography tools creates more space for creativity, handling the busy work so photographers can focus on the craft. If you care about craft, community, and what technology can unlock for creative people, this is the work. We're a mission-driven and focused company where your work ships quickly, is meaningful, and reaches tens of millions of people worldwide. You'll have a real say in what we build and how we build it. We hire people who don't wait to be asked, naturally connect the dots, care about the quality of what they ship, and believe the best outcomes come from building together. About The Role We’re looking for a Senior Software Engineer, Infrastructure to own the platform that VSCO product and data teams ship on. You’ll join a small infra team that treats AWS, EKS, and GitOps as the default path for new systems, and you’ll spend real time pairing with other teams so - search, Workspace, and data - land in the right Terraform, Helm, and Flux instead of one-off snowflakes. This is a hands-on senior seat. You will design Terraform modules, cut production traffic to EKS, secure traffic with Cloudflare, look for optimizations in our AWS infrastructure, and leave on-call better than you found them. You like production ownership, you can sequence

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. We’re looking for a Senior Software Engineer to join our Network Engineering team to accelerate building and scaling our innovative systems that support our growing identity platform. In this role, you will build the next-generation infrastructure that underpins all systems at CLEAR. The ideal candidate for this role will approach challenges with an eye toward reliability, simplicity, and scalability. What You'll Do: Develop and maintain a streamlined process for engineers to effortlessly build and deploy scalable and reliable software-defined networking solutions on AWS. Enhance our compute platform (Kubernetes) by integrating new functionalities and features, focusing on AWS networking services and concepts such as VPCs, Route Tables, Security Groups (SGs), ALBs/ELBs, and Route53, as well as implementing Kubernetes networking solutions like service mesh (Istio) to optimize service communication and management. Collaborate across engineering teams to advocate for and implement best practices in observability, utilizing tools like Splunk or Datadog to ensure robust network monitoring. Act as a product owner for our infrastructure, collecting feedback and requirements from engineering teams to address pain points and develop solutions, particularly in the realm of AWS networking and cloud-native design principles. What you're great at: 6+ years of extensive experience in infrastructure and platform development, particularly in software-defined networking and AWS cloud services. Proficient in writing production-grade softwar

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. We’re looking for an early career Software Engineer to join our Infrastructure team to accelerate building and scaling our innovative systems that support our growing identity platform. In this role, you will build the next-generation infrastructure that underpins all systems at CLEAR. The ideal candidate for this role will approach challenges with an eye toward reliability, simplicity, and scalability. What You'll Do: Develop and maintain a streamlined process for engineers to effortlessly build and deploy scalable and reliable software-defined networking solutions on AWS. Enhance our compute platform (Kubernetes) with new functionalities and features, focusing on AWS networking services and concepts such as VPCs, Route Tables, Security Groups (SGs), ALBs/ELBs, and Route53, optimize service communication and management. Collaborate across engineering teams to advocate for and implement best practices in observability, utilizing tools like Splunk or Datadog to ensure robust network monitoring. Act as a product owner for our infrastructure, collecting feedback and requirements from engineering teams to address pain points and develop solutions, particularly in the realm of AWS networking and cloud-native design principles. What you're great at: 0-2 years of experience in infrastructure and platform development and AWS cloud services. Proficient in Python, with understanding of Kubernetes and container orchestration tools like EKS and ECS. Understand AWS networking services, including VPC design, SGs, NATGWs, ALBs/ELBs, Rout