Infrastructure Support Engineer Jobs

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Everpure (formerly Pure Storage) is hiring a Senior Pre-Sales Systems Engineer to support our Higher Education business, with a focus on R1 research universities. R1 institutions are not one customer. A single campus can behave like a dozen different organizations at the same time: central IT running enterprise applications, research computing and HPC teams, genomics and imaging cores, AI and machine learning labs competing for GPU time, an academic medical center with its own rules and its own budget, and faculty groups buying infrastructure directly with grant money. Decisions move through CIOs, research computing directors, principal investigators, sponsored programs offices, procurement, and consortium contract vehicles, often in parallel and not always in agreement. That environment rewards someone who can hold a lot of context at once, translate between very different audiences, and connect technology to the outcomes these institutions actually care about: time to result for researchers, compliance with sponsor and grant requirements, data that stays usable for a decade or more, and budgets that have to stretch further every year. You will be the technical lead on these accounts, working alongside account managers, specialists, and partners to build solutions customers can defend internally, both technically and financially. Location: MA / NY / PA WHAT YOU'LL DO Develop a real understanding of what drives ea

About Mach Industries Founded in 2023, Mach Industries is a rapidly growing defense technology company focused on developing next-generation autonomous defense platforms. At the core of our mission is the commitment to delivering scalable, decentralized defense systems that enhance the strategic capabilities of the United States and its allies. With a workforce of approximately 350 employees, we operate with startup agility and ambition. Our vision is to redefine the future of warfare through cutting-edge manufacturing, innovation at speed, and unwavering focus on national security. We are dedicated to solving the next generation of warfare with lethal systems that deter kinetic conflict and protect global security. The Role Mach Industries is seeking a New Graduate Software Engineer to develop software for next-generation autonomous defense systems. Depending on your experience and interests, you may contribute to embedded software, firmware, flight software, autonomy, simulation, developer infrastructure, or mission applications. You will collaborate with engineers across avionics, GNC, systems, test, and hardware to build, integrate, and deploy reliable software on real-world platforms. This role is ideal for a hands-on engineer who enjoys solving challenging technical problems, learning across disciplines, and taking ownership of software from initial development through testing and deployment. Key Responsibilities Develop, test, and maintain software for autonomous aircraft, missiles, propulsion systems, and related defense platforms. Write clean, efficient, and well-tested code in C, C++, Rust, Python, or similar languages. Contribute to one or more technical areas, including embedded software, firmware, flight software, autonomy, simulation, mission applications, and developer infrastructure. Collaborate with avionics, GNC, systems, test, and mechanical engineers to support hardware-software integration. Build tools, automated tests, and simulation environmen

About the Team The Industrial Compute team is responsible for building the physical infrastructure that powers OpenAI’s largest-scale AI systems. We design, deploy, and operate next-generation compute infrastructure across a rapidly expanding global footprint, combining OpenAI-owned infrastructure with strategic cloud and infrastructure partners to support frontier AI workloads. As our infrastructure footprint grows, operational excellence across third-party providers becomes increasingly critical. Our team ensures external infrastructure partners consistently deliver the reliability, performance, and operational maturity required to support OpenAI’s rapidly expanding compute environment. About the Role We are seeking a Hardware Technical Program Manager, Infrastructure Partner Operations to lead operational delivery across OpenAI’s third-party infrastructure partners, including major cloud service providers and strategic compute vendors. In this role, you will serve as the primary operational program manager for external infrastructure partners, driving accountability for service delivery, operational readiness, incident management, performance reporting, and continuous operational improvement. You will work closely with partner engineering and operations teams while coordinating internally across Hardware Engineering, Infrastructure Operations, Capacity Planning, Networking, Supply Chain, Deployment, Reliability Engineering, and executive leadership. Success in this role requires someone who understands how hyperscale infrastructure organizations operate, can establish strong operational governance with external partners, and is comfortable driving complex technical programs without direct ownership of the underlying infrastructure. Key Responsibilities Own operational engagement with third-party infrastructure providers, ensuring consistent execution against operational commitments, service-level agreements (SLAs), and performance expectations. Develop operationa

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 Senior Data Engineer, you will work to define the data ontology for all of Roblox, establish standard methodologies for data operations and lifecycle management, design and build analytics tooling and frameworks, and influence event instrumentation. Additionally, this role is highly multi-functional, requiring close collaboration with Data Science, Experimentation, and Machine Learning teams to understand customer requirements and analytics applications, as well as with Data Infrastructure and Storage teams to develop integrated solutions. Join us and be a part of a dynamic team driving innovation and growth at Roblox. This role will report to our Engineering Manager on the DSE team. You Will: Partner with Data Science, Product, and Engineering to collect requirements to define the data ontology for all of Roblox Lead and mentor a growing team of Data Engineers to support Roblox's ever-evolving data needs Design, build, and maintain efficient and reliable batch and streaming data pipelines to populate core data sets Develop scalable frameworks and tooling to automate analytics workflows and streamline users interactions with data products Establish and promote standard methodologies fo

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

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . As a Group Product Manager on the Financial Engineering team within Platform , you'll define how Coinbase's finance infrastructure scales to support hundreds of billions of dollars in annual transaction volume. This team empowers every finance function at Coinbase to operate with precision, agility, and foresight, and you'll own the product strategy for finance transformation, automation, and AI-driven tooling. This is a high-visibility role with direct exposure to Coinbase's Chief Accounting Officer, and you'll lead a team of PMs to deliver mission-critical systems across accounting, treasury, and financial reporting. What you'll do: Own the product strategy and roadmap for finance transformation, including process automation, AI-driven insights, and system modernization, ensuring alignment with Finance leadership priorities and company-wide objectives. Lead and develop a team of product managers, setting the bar for product craft, stakeholder management, and technical depth across the Financial Engineering organization. Drive cross-functional execution of high-impact initiatives spanning reconciliation tooling, SOX-compliant change management for the financial reporting pipeline, new product finance onboarding, and self-serve tools for Accounting and Treasury. Partner directly with senior leaders in Finance, Product, and Engineering to prioritize a portfolio of ini

About the Team Identity is the foundation of trust in an AI-powered world. As people build a rich personal and organizational context in ChatGPT, they need systems that protect it, remember it, and let them share it securely across apps and agents. Without strong identity, context stays locked away or exposed. With it, AI becomes safe, personal, and truly useful, empowering users while keeping control firmly in their hands. Our team builds the trusted OpenAI account layer that connects people, enterprises, developers, and agents to OpenAI apps and the broader AI ecosystem. Our systems are the front door to OpenAI—held to an exceptionally high bar for availability, security, and latency—and are depended on by many internal teams. About the Role As an Engineering Manager, Identity Platform you will lead a team owning foundational identity services that must be highly reliable, secure, and fast under extreme load. You’ll set direction, grow and support the team, and partner closely across engineering and security to strengthen the platform that enables trusted access to OpenAI products. In this role, you will: Build, lead, and develop a high-performing engineering team. Coach and mentor engineers and senior technical leads to increase their impact and support their growth. Define and own the technical strategy, roadmap, and execution for OpenAI’s core identity systems. Guide the architecture of distributed systems operating at massive scale, with high requirements for reliability, privacy, and performance. Partner closely with Product and Infrastructure teams to support new product needs and uphold high system standards. Ensure the team operates effectively, maintains strong engineering rigor, and consistently delivers against ambitious goals. Establish processes and a culture that enable fast learning, high trust, and responsible innovation. Lead the team responsible for the authentication stack and token exchange infrastructure, ensuring high availability, strong sec

About The Role Together AI is rapidly scaling its compute infrastructure across multiple sites and deployment types. The Associate, Infrastructure Strategy & Operations will be the analytical backbone of the Infrastructure Strategy team, powering the research, benchmarking, and operational analysis across the team's core workstreams, including capacity planning, compute sourcing, vendor evaluation, and site selection. You'll be the person who keeps the team organized and well-informed as infrastructure scales, partnering closely with Infra Eng and Finance to ensure timely, data-backed decisions. Responsibilities Support the Infrastructure Strategy team's planning process by gathering data, running comparisons, and preparing materials and recommendations for leadership reviews. Build internal trackers and dashboards that help the team monitor infrastructure deployments, vendor pipelines, and compute allocations across products and customers Maintain and improve the team's sourcing comparison frameworks across location, vendor, and site evaluation workstreams, in partnership with Finance and Infra Eng. Run analyses to support capacity allocation decisions. Research and evaluate data center sites and energy sourcing options, comparing power availability, connectivity, permitting timelines, deployment readiness, and reliability. Champion process improvements across the Infrastructure Strategy function, collaborating cross-functionally with Engineering, Data, and Finance to design AI-native workflows that streamline operations and automate repetitive analysis. Take on ad hoc analytical projects as priorities evolve, operating with speed and minimal direction. Requirements 3+ years of experience in management consulting, business operations, strategy, or a similar analytically rigorous role. Proficiency in Excel/Google Sheets, familiarity with SQL or data visualization tools, and comfort with AI productivity tools (e.g., Claude Code, Codex). Strong quantitative skills

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g., Seaborn , Luigi ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. About the Role: We’re looking for our first IT Lead to build and own the systems that enable everyone at Modal to work effectively and securely. You’ll own our employee technology environment end-to-end, including identity and access, devices, internal systems, SaaS applications, and day-to-day IT operations. You’ll work closely with Security and Engineering to build an environment that is secure by default, easy to operate, and scales with the company. This is initially a hands-on role. You’ll build systems, automate workflows, and solve problems directly. As Modal grows, you’ll define how the IT function should scale and eventually build a team around it. What You’ll Work On: Identity & Access Own employee identity and access across internal systems and SaaS applications Build scalable onboarding, offboarding, and access lifecycle workflows Improve SSO, MFA, least privilege, and access management in p

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g., Seaborn , Luigi ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you'll be working on the distributed object storage system that underpins every container image, volume, and checkpoint on Modal: hundreds of petabytes of data, replicated across multiple cloud object stores and a CDN, cached on local NVMe across a large fleet of workers in many datacenters, and shared peer-to-peer within each datacenter. You'll make cold starts feel local when the data is hundreds of milliseconds away, designing the caching, preloading, and peer-to-peer layers that hide object-store latency and keep public ingress off saturated uplinks. You'll own durability and cost at petabyte scale, from streaming and batch replication between origins, to garbage collection over billions of objects. You'

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g., Seaborn , Luigi ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We’re looking for strong engineers with experience building software that developers love to work with. Our ideal candidate is someone with a demonstrated drive to build beautiful abstractions that enhance developer productivity. Requirements: 5+ years of experience developing high-quality Python, JS or Go applications or libraries where the code is used or interacted with by other developers A strong code-as-product sense that manifests as a focus on developer ergonomics and productivity. Knowledge of async programming and concurrency management/pitfalls A high level of customer empathy, good communication skills, and an openness to working directly with our users to help solve their problems. Ability to participate in on-call rotation and respond to production incidents. Ability to work in-person in our New York or Stockholm office. Any of the following would be a plus: Having built developer to

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g., Seaborn , Luigi ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: Modal’s Inference Runtime team owns the container runtime stack used to run inference and training workloads across our fleet. We work at the boundary of Linux, containers, filesystems, storage, GPU drivers, and distributed systems.Our goal is to make demanding ML workloads start quickly, run efficiently, and remain securely isolated — whether they use a single GPU, hundreds of gigabytes of memory, or multiple GPUs connected with RDMA.We’re looking for a systems engineer who enjoys working deep in the stack. You’ll build production runtime infrastructure in Rust and Go, diagnose difficult Linux and performance problems, and help determine the architecture of Modal’s container platform. You’ll also work closely with maintainers of gVisor and contribute to the runtime itself when the right fix belongs upstream. The Work: Make container startup, checkpoint, and restore dramatically faster for large i

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for a strong technical lead to guide the engineers designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. You'll lead the team responsible for the distributed object storage system that underpins every container image, volume, and checkpoint on Modal: hundreds of petabytes of data, replicated across multiple cloud object stores and a CDN, cached on local NVMe across a large fleet of workers in many datacenters, and shared peer-to-peer within each datacenter. You'll set technical direction for the primitives that other teams (filesystems, training, sandboxes) build on, balancing durability, latency, throughput, and cost. You'll own the roadmap from today's hardest problems (garbage collection at petabyte scale, active-active replication, rate limiting that protects the upstream without wasting ut

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for a strong technical lead to guide the engineers designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. You'll lead the team responsible for Modal's machines layer: the fleet of bare metal and cloud hosts that every Function, Sandbox, and training job runs on, and the control plane that provisions, images, monitors, and repairs them. You'll own the full lifecycle of a machine, from accepting and benchmarking new hardware from a growing set of providers, to network bring-up, kernel and image management, GPU and disk health tracking, and automated remediation of unhealthy hosts. You'll manage a team of 3–8 engineers while staying hands-on across the stack which involves BMCs, firmware, PXE, bootloaders, Linux networking, drivers, and distributed control-plane services, and you'll shape our long-

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g., Seaborn , Luigi ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you'll be working on Modal's machines layer: the fleet of bare metal and cloud hosts that every Function, Sandbox, and training job runs on, and the control plane that provisions, images, monitors, and repairs them. You'll automate the integration of new capacity from a growing set of hardware providers; from auditing and benchmarking hosts and clusters, to maintaining our machine images, configuring GPUs, RDMA, networking, and storage, and getting machines into production. You'll build the automation that keeps the fleet healthy without human intervention: detecting bad GPUs, thermals, and disks. You'll dig into whatever is between the hardware and the software that runs on top of it, whether that is a kern