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 The FlashArray team builds the industry’s most innovative, high-performance, and highly available portfolio of products that are designed for the most demanding mission-critical applications. While we deliver a hardware storage array, over 90% of our engineering staff are software engineers. Our customers are the most important part of our business, and they love FlashArray for its simplicity of management, the constant flow of new and exciting upgrades, and the ability to live on the cutting edge of technology while never taking downtime, ever. Most recently, we extended the value of our FlashArray capabilities into the cloud with CloudSnap and Cloud Block Store for AWS. These new innovations enable our customers to leverage the agility of the public cloud for both traditional IT and cloud-native applications. This particular role is for a security-minded software engineer. WHAT YOU'LL DO Design and implement creative new algorithms and technologies for high-performance, highly reliable systems (think six 9’s) Own and deliver FlashArray product security features end-to-end, from concept to shipped product Analyze and solve challenging problems through persistence and insight, with an eye toward making FlashArray more secure Work as a team with smart peers who inspire you and who are inspired by you Make customers really happy, because that’s why we do what we do Learn a ton, whether you know a lot, or nothi
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It Storage Engineer Jobs
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About the Role The worldwide data management software market is massive – IDC forecasts it to be $137.6 billion by 2026! At MongoDB, we are transforming industries and empowering developers to build amazing apps that people use every day. We are the leading modern data platform and were the first database provider to IPO in over 20 years. Join our team and be at the forefront of innovation and creativity. The Storage Layer Services Team is currently re-architecting the MongoDB Cloud Storage Layer. This is a relatively new team in MongoDB that sits at the heart of the next generation MongoDB Cloud Storage Architecture, and the team is working to build performant multi-tenant distributed storage services both to enhance our existing MongoDB cloud storage architecture and to power more of our customers' use cases more efficiently. We are looking for talented Senior Engineers to join the team and be founding members of the team, where you will play a crucial role in our multi-year roadmap. Our team champions a strong culture of inclusivity, diversity, and collaboration. If you want to work on a collaborative team that applies distributed systems fundamentals to deliver core storage features of a popular database, join us! Let’s change what’s possible for application developers, system architects, and database operators. We are looking to speak to candidates who are based in Sydney for our hybrid working model. Candidate Profile Minimum of 5 years of experience in programming, debugging, and performance tuning of distributed and/or highly concurrent software systems Strong systems fundamentals, including multi-threaded programming and performance profiling Experience with distributed systems Proven experience in building, deploying, and operating multi-tenant cloud services with a focus on operational excellence Familiarity with database internals or experience building core components for data processing systems Hands-on experience in developing performance-sensitive so
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 The Platform Engineering team creates the foundation that enables the industry’s most innovative, high-performance, and highly available portfolio of Pure Storage products that are designed for the most demanding mission critical applications. We design, build and deliver hardware products, but over 90% of our engineering staff are software engineers. Our customers are the most important part of our business and they love our products for the simplicity of management, the constant flow of new and exciting upgrades, and ability to live on the cutting edge of technology while never taking downtime, ever. Pure's product portfolio enables our customers to leverage the agility of the public cloud for both traditional IT and cloud-native applications. WHAT YOU'LL DO Deliver manufacturing diagnostics and tools for Everpure Direct Flash Module product line Collaborate with hardware, firmware, software and manufacturing test teams, and deliver support for our ambitious roadmap items. Collaborate with product managers and engineering teams in getting requirements. Responsible for the overall development life cycle of the solution and managing projects. Instill best practices of software development and documentation, assure designs meet requirements and deliver high quality work on tight schedules. Clearly and regularly communicate status on how projects are progressing. Managing day-to-day software engineering devel
Backblaze is the object storage leader in the open cloud movement, fueling customer success with cloud storage built purposefully to unlock budgets, unburden administrators, and unleash innovators. Together with our partners, we’re helping customers break free from the restrictive, overpriced legacy solutions that hold them back, and blaze forward with the full power of the open cloud in their hands. Founded in 2007, we scaled the business with less than $3 million in outside funding until 2021, when we did a traditional IPO on the Nasdaq stock exchange. Today, Backblaze generates over $100m in revenue and is the leading specialized storage cloud - managing over three billion gigabytes of data storage for 500K+ customers in 175+ countries, including businesses, developers, IT professionals, and individuals. But while there is a lot to celebrate in our past, there is almost as much opportunity ahead of us. We are seeking a Sr. AI Security Engineer to join our team! About The Role Backblaze is seeking a Senior AI Security Engineer to design and implement safeguards for internal AI usage , with a focus on agentic systems, developer protection, and runtime security . This is a hands-on role for a practitioner who has built and deployed security controls , not just defined policy. You will enable teams to safely use AI by creating enforcement layers, identity controls, and detection capabilities that constrain and monitor AI-driven activity. What You’ll Do: Agentic AI Safeguards Architect and implement guardrails for tool-using AI systems , including: Tool access controls and allowlists Context and memory isolation Step-level validation of agent actions Apply mitigations aligned to the OWASP Agentic AI Top 10 (e.g., prompt injection, unsafe tool use, data leakage, excessive autonomy) Runtime Security Controls Build enforcement mechanisms that govern AI behavior at execution time: Interceptors, proxies, or middleware for tool/API calls Policy decision and enforcement laye
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 1touch.io is a technology company focused on automated, real-time discovery, mapping, and tracking of sensitive personal data. Its AI-powered platform helps enterprises improve data privacy, security, and governance across complex on-premises and cloud environments. Together, 1touch.io and Everpure transform enterprise data from passive storage into an intelligent, context-aware, and governed foundation - making it AI-ready at the source so organizations can securely understand, trust, and activate their data at scale. As a Java Engineer, you will design and deliver core platform capabilities that help organizations discover, classify, and protect sensitive data across complex environments. You will work on highly scalable backend systems, collaborating with engineering, product, and customer-facing teams to solve challenging technical problems where performance, resilience, and precision matter. WHAT YOU'LL DO Design and build software that discovers, classifies, and safeguards sensitive data across diverse environments and platforms. Lead the design, implementation, testing, deployment, and continuous improvement of platform capabilities. Develop reliable, scalable, and high-performing backend systems designed for complex, real-world operating environments. Extend platform capabilities by integrating new data sources, storage systems, and services. Solve engineering challenges related to scale, concurrency, perf
NVIDIA Networking division is a leading supplier of innovative end-to-end InfiniBand and Ethernet connectivity solutions and services for servers and storage. We offer market-leading solutions that include adapter cards, switches, cables, and software to support networking technologies. Our products optimize Data Center performance and deliver industry-leading bandwidth and scalability. In addition, we serve a wide range of sectors including high performance computing, enterprise, Data Center, cloud computing and Web 2.0. We are constantly reinventing ourselves to stay ahead of the market and bring groundbreaking products and services to the industry. Our product line is focused on delivering the most optimized Ethernet solutions for industries like Media and Entertainment as well as any other industry that can benefit from our DataStream and TCP/IP acceleration. What you will be doing: Drive multiple early-stage design concepts of Test Equipment & fixtures while working in fast-paced product development cycles. Independently lead Test Equipment & fixtures design from concept, through detailed design, and support it during Bring-up, Qualification and Mass-Production phases. Participate and lead design and design reviews of Test Equipment & fixtures by using our CMs (Contract Manufacturers) as the designers Collaborate in research of groundbreaking technologies, materials, and processes with other groups to bring in creative ideas that address evolving needs. What we need to see: B.Sc. in Mechanical Engineering or higher degree. 5+ years of experience in classical mechanical design of mechanisms, jigs, fixtures, products and machines development. Knowledge and experience in automation (pneumatics XYZ motion systems, etc) and in design of machining and sheet metal parts Knowledge and experience in static analysis and simulations.
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're looking for Forward Deployed ML Engineers who want to work at the intersection of deep technical work and direct customer impact. As an ML FDE, you'll partner with leading AI companies and foundation model labs to help them achieve state-of-the-art performance on their most demanding workloads — LLM serving, model training (SFT, RLHF), audio pipelines, scientific computing, and more. You're helping teams reach outcomes most engineers can't on their own. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the AI stack, and energy for working directly with customers on hard problems. You will: Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and optimize production AI workloads
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're looking for Forward Deployed Engineers on our engineering team who want to work at the intersection of deep infrastructure work and direct customer impact. As an FDE, you'll partner with leading AI companies and foundation labs on cloud architecture, networking, storage, containerization, sandboxing, and more — helping them design and ship production infrastructure on Modal's platform. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the infrastructure stack, and energy for working directly with customers on hard problems. You will: Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and deploy massive-scale production workloads on Modal Lead technical discovery and architect
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: Modal is seeking an experienced Forward Deployed Engineer (FDE) to partner with our sales team and drive technical sales success. As an FDE, you will be the technical voice in our sales process, working directly with Account Executives to help enterprise customers understand how Modal can transform their AI/ML infrastructure. You will: Partner with Account Executives to identify, qualify, and close strategic enterprise opportunities Lead technical discovery sessions with prospective customers to understand their current infrastructure, pain points, and requirements Design and present compelling technical solutions that demonstrate how Modal addresses customer needs Architect migration paths from existing cloud infrastructure (AWS, GCP, Azure) to Modal's serverless platform Conduct technical demos, experiments, and proof-of-concepts that showcase Modal's capabilitie
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: Modal builds AI infrastructure products that developers love. That's how we grew so quickly and why word-of-mouth remains one of our most important channels today. From powering one of the largest vibe-coding platforms at Lovable to enabling teams like Ramp to build their own internal coding agents , Modal Sandboxes are used by developers to safely execute AI-generated code at scale. We're now hiring our first developer relations engineer focused on Modal Sandboxes. Whether it’s banger tweets , in-depth technical resources or long-form talks , we want to meet developers by any medium necessary and empower them to build and ship novel AI products. In this role, you will primarily be creating and distributing technical content that is unique, educational, and practical. This content will be the first Modal touchpoint for many of our users. We want to not only showcas
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're looking for Forward Deployed ML Engineers who want to work at the intersection of deep technical work and direct customer impact. As an ML FDE, you'll partner with leading AI companies and foundation model labs to help them achieve state-of-the-art performance on their most demanding workloads — LLM serving, model training (SFT, RLHF), audio pipelines, scientific computing, and more. You're helping teams reach outcomes most engineers can't on their own. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the AI stack, and energy for working directly with customers on hard problems. You will: Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and optimize production AI workloads
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’re looking for an Infrastructure Security Engineer to design and secure the core systems that power our platform. This role focuses on building security directly into our infrastructure—from container isolation and orchestration to identity and secrets management in a multi-tenant, cloud-native environment. You’ll work closely with engineering teams to define secure primitives and ensure our platform is resilient, scalable, and trustworthy by design. This is a hands-on, deeply technical role focused on real systems, not compliance or policy. What You'll Do: Platform & Runtime Security Design and improve isolation mechanisms for multi-tenant workloads (containers, sandboxing, execution environments) Strengthen boundaries between customers, workloads, and internal systems Identify and mitigate risks in distributed, dynamic compute environments Container &
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: Modal builds AI infrastructure products that developers love. That's how we grew so quickly, and why word of mouth remains one of our most important channels today. In this role, you will primarily create and distribute technical content that is unique, educational, and practical. This content will be the first Modal touchpoint for many of our users. We want to not only showcase the power and developer experience of Modal, but also serve as a trusted resource for them when implementing new AI technologies. In this role, you will: Distill the latest advancements in AI technology and educate developers on how to incorporate them. Give demos/talks about Modal and adjacent tools at developer events. Engage with users in our community, both online (X, LinkedInReddit, Slack) and at in-person events. Build relationships, integrations, and joint marketing activities with o
About the Team The Core Services team is responsible for building and managing foundational services. It acts as the bridge between core infrastructure (e.g. compute, storage, networking) and product engineering teams, and enables product teams to move fast, build reliably, and scale efficiently. About the Role As a software engineer in the core services team, you will design and operate critical backend platforms such as caching systems, workflow orchestration, metadata stores, and file services. You’ll focus on building highly reliable, scalable, and performant systems that serve as the backbone of our products. We’re looking for people who are passionate about building infrastructure that empowers product teams, love working on distributed systems challenges, and enjoy creating well-designed APIs and abstractions that accelerate development. 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, build, and maintain shared infrastructure services such as caching layers, workflow orchestration (Temporal), metadata stores, and file storage services. Collaborate with product teams to provide scalable, reliable primitives that abstract the complexities of distributed systems. Improve performance, resilience, and scalability of core services that power customer-facing applications. You might thrive in this role if you: Have experience with distributed systems, caching infrastructure (e.g., Redis, Memcached), metadata storage (e.g., FoundationDB), or workflow orchestration (e.g., Temporal, Cadence). Have experience running containerized services in cloud environments and integrating them into automated build/test/release (CI/CD) workflows. Understand trade-offs in consistency models, replication strategies, and performance optimization in multi-region systems. Excel at communication and collaboration with cross-functional teams, and are obsesse
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. About Modal Data: We’re growing our Data team and are looking for our first few key hires to build self-serve data tools and drive business strategy in the right direction. The mission of the Modal Data team is to make it easy to track company goals, make evidence-backed decisions, and prioritize the right work. We do this via: Self-serve AI analytics tools (Hex, Snowflake) Embedding with teams as a “data adviser”, providing strategic analysis and consulting What You'll Do: Contribute to building the most modern analytics stack in Data today to support AI-driven self-serve analysis, key metrics tracking, and external customer reporting Influence work on new products like LLM Inference Endpoints through product analytics tracking Identify millions of dollars of cost savings and optimization across our tools and financial operations Write data pipelines that power the operatio
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