Senior Infrastructure Automation Engineer in United States

Become a part of our caring community The Principal Storage Engineer is a senior technical leader responsible for defining and advancing the enterprise storage architecture and long-term data infrastructure strategy. This role establishes standards, develops five-year technology roadmaps, and designs secure, resilient, scalable, and cost-effective storage platforms for business-critical, analytics, and artificial intelligence workloads. The engineer serves as the organization’s storage subject-matter expert and partners with infrastructure, cloud, security, data, application, architecture, finance, and vendor teams to translate business requirements into sustainable technology capabilities. The Principal Storage Engineer is a senior technical leader responsible for defining and advancing the enterprise storage architecture and long-term data infrastructure strategy. This role establishes standards, develops five-year technology roadmaps, and designs secure, resilient, scalable, and cost-effective storage platforms for business-critical, analytics, and artificial intelligence workloads. The engineer serves as the organization’s storage subject-matter expert and partners with infrastructure, cloud, security, data, application, architecture, finance, and vendor teams to translate business requirements into sustainable technology capabilities. Key Responsibilities Define the enterprise storage vision, reference architecture, engineering standards, and five-year roadmap across block, file, object, software-defined, and hybrid storage services. Lead architecture decisions for on-premises AI infrastructure, including high-throughput and low-latency storage fo

Who we are About Stripe Stripe is a technology company that builds economic infrastructure for the internet. Businesses of all sizes—from new startups to public companies like Amazon and Salesforce—use our software to accept online payments and run technically sophisticated financial operations in more than 100 countries. By helping businesses accept payments from anywhere in the world and accelerating the economic shift from offline to online, we aim to increase the GDP of the internet. About the team Stripe’s Leadership Recruiting Team (LRT) is a high-performing group of strategic and creative problem solvers. We are passionate about finding and hiring the very best leaders and experts from around the globe to help drive the next arc of Stripe’s growth. What you’ll do In this role, you will be directly responsible for partnering with senior stakeholders to identify, attract, assess, and hire individuals for leadership roles across the company. Responsibilities Strategically partner with executives to hire top talent for Stripe’s highest priority engineering leadership roles Define, design, and implement recruiting processes and search engagements for a variety of senior leadership roles. This includes understanding and mapping the talent landscape, internal calibration and referrals, and matching those data points with the external talent supply Manage end-to-end leadership-level searches from inception of candidate contact to onboarding, including research, outreach strategies, candidate experience, negotiations, partnering with HR for successful onboarding, and communicating with stakeholders along the way Collaborate with cross-functional partners, such as People Partners, Compensation, and Business Leads, to align hiring goals with business needs Develop competency-based interviews that surface a candidate’s full range of capabilities, explore their aspirations, and gain insight into how their experience will apply to a leadership role at Stripe Fo

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 The Events Analytics Platform (EAP) team is responsible for the infrastructure that powers all of Sentry's time-series data and searching capabilities across billions of events with sub-second latency. We started this initiative by building Snuba, the primary storage and query service for Sentry's event data powered by ClickHouse, and we are now focused on unlocking deeper visibility and reporting across the terabytes of event data our users generate. As a Senior Software Engineer, you will lead efforts to push the boundaries of data visibility at Sentry. You will do this by expanding the capabilities of our search infrastructure, building new capabilities on top of our state-of-the-art storage layer and increasing the performance and integrity of Sentry’s core data services. You will also help shape Infrastructure's technical direction at Sentry and collaborate with Product and other Engineering teams to turn that vision into a reality. If you want to solve the hard problems that come with scaling event data into the petabyte range, this could be the job for you. In this role you will: Expand EAP's ability to deliver data at world-class speed and reliability. Architect and automate services and systems to scale reliably under growing demand. Make architectural trade-offs that balance product requirements with engineering constraints. Maintain and grow the team's code quality initiatives by regularly reviewing code and contributing to design decisions. Lead design and discussions around deliverables the team is working towards. Improve the maintainability and developer experience of the codebases EAP owns. Exa

As a Cloud Security Engineer you will partner with different stakeholders across the organization to secure our cloud infrastructure. As part of the Platform Security organization we secure the building blocks of Datadog’s applications and infrastructure. We do this by building solutions to solve systemic risks and combine an approach of making the secure path easier and the insecure path harder to secure and accelerate the business. We regularly partner with the most bleeding edge internal products and are working to solve and build solutions to enable our safe usage of AI. We also develop AI based solutions to enable security at scale. We are looking for a Service Mesh and Kubernetes focused security specialist to help round out an incredibly strong infrastructure security focused group. You will rotate through a variety of internal projects and gain deep exposure to Datadog’s infrastructure. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Solve our most challenging cloud infrastructure security problems starting with our core building blocks and golden paths. Enable our engineers to build and ship secure solutions quickly. Build and extend Datadog’s Platform Security solutions. Leverage and influence the direction of Datadog’s products to secure our infrastructure, and provide internal feedback that enables our teams to improve the products for ourselves and our customers. Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or related scientific field or equivalent professional experience. Passionate about advocating for and implementing solutions to complex problems, at-scale, in a large multi-cloud environment. You don’t want to just provide security recommendations, you want to help imple

Job Details: Job Description: Intel is shaping the future of technology to help create a better future for the entire world. Our work in pushing forward fields like AI, analytics, and cloud-to-edge technology is at the heart of countless innovations. With a career at Intel, you'll have the opportunity to use technology to power major breakthroughs and create enhancements that improve our everyday quality of life. Join us and help make the future more wonderful for everyone. Want to learn more? Visit our YouTube Channel or the link below. Life at Intel The Role and Impact As a System Software Architect, you will play a pivotal role in designing and developing innovative software solutions that drive efficiency and scalability across Intel's manufacturing processes. You will be responsible for architecting robust systems and frameworks that enhance operational performance while ensuring seamless integration with existing technologies. Your contributions will directly impact Intel's ability to deliver world-class semiconductor products efficiently and reliably. Business Group Intel Foundry Services is at the forefront of manufacturing excellence, delivering cutting-edge solutions to meet the complex demands of the semiconductor industry. The group focuses on pioneering advancements in manufacturing technologies, infrastructure optimization, and secure operations, enabling Intel to stay ahead in a fast-evolving landscape. By joining this team, you will contribute to Intel's broader mission of solving technological challenges and empowering innovation worldwide. Key Responsibilities: - Architect scalable and efficient system sof

The DFP Engineer – Manufacturing role defines and implements the validation and screening of new silicon features within high‑volume manufacturing flows. You will translate product requirements into executable test methodologies, infrastructure, and detailed manufacturing test plans that ensure quality, yield, and efficiency at scale. This role sits at the intersection of multiple multi-functional teams to make manufacturing test an outstanding part of the overall codesign and DFP lifecycle. What you will be doing: Own end-to-end manufacturing test methodology across all test stages. Translate system specs and product POR into DFP requirements, test content, coverage, and flows. Define and maintain the DFP roadmap, including infrastructure and turning point planning. Partner multi-functionally to implement test content, debug hooks, and coverage improvements. Drive alignment on manufacturability, test time, binning strategies, and cost vs. coverage trade-offs. Embed testability requirements into design to enable robust screening and debug. Define data and analytics frameworks to support yield analysis and continuous improvement. Lead DFP documentation as the single source of truth and feed findings into future methodologies. What we need to see: MS in Electrical Engineering, Computer Engineering, or related field (or equivalent experience) 6&#43; years in silicon post‑silicon validation and/or high‑volume manufacturing test for complex SoCs, GPUs, CPUs, or similar. Hands‑on experience with test content bring‑up, limit setting, correlation to characterization, and yield/coverage optimization. Proficiency with scripting and data analysis (e.g., Python, MATLAB, R, SQL) for test data analytics, limit tuning, and yield/debug analysis. <

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a Staff Hardware Engineer to provide advanced operational, diagnostic, and engineering support for Graphcore’s Arm-based hardware platforms across lab and data center environments. This role focuses on supporting hardware bring-up, validation, and troubleshooting of complex AI compute platforms, including server blades, racks, and rack-scale infrastructure. The successful candidate will collaborate closely with engineering, platform, and data center teams to ensure the reliability and performance of next-generation AI systems. The Team The Systems Engineering and Hardware Engineering teams are responsible for enabling the bring-up, validation, and operational reliability of Graphcore’s AI infrastructure platforms. The team works closely with server engineering, firmware teams, platform architects, and data center operations to support the development, testing, and deployment of next-generation AI compute systems. This collaborative environment enables rapid problem-solving and continuous improvement of Graphcore’s hardware platforms from early development through production deployment.

NVIDIA’s DGX Cloud organization is seeking a Senior Data Engineer to become part of its data team! We develop the reliable data foundation that supports fleet health, capacity, utilization, cost, reliability, and operational decision-making throughout DGX Cloud. Our platform supports engineering, operations, finance, and product teams managing and expanding large GPU fleets across cloud service providers and NVIDIA Cloud Partners. We are looking for a practical engineer and technical lead to take charge of a key part of the Navigator data platform. We develop the systems that transform distributed infrastructure telemetry and operational data into dependable, managed data products that support fleet health, capacity, utilization, cost, and operational decisions. We are seeking a hands-on, platform-minded engineer to build and evolve the systems that turn distributed infrastructure telemetry and operational data into reliable, governed data products. You will work across ingestion, transformation, data quality, platform architecture, security, observability, and self-service consumption to help make Navigator and the DGXC data platform a dependable source of truth. We do expect strong engineering fundamentals, experience operating production systems, and the ability to learn new platforms and domains quickly. What you'll be doing: Own systems end to end. For example, work from ambiguous customer and operational needs through architecture, implementation, deployment, observability, incident response, and ongoing support. Construct data pipelines and products. Such as designing and maintain batch and streaming ingestion, transformation, reconciliation, and serving paths for fleet, capacity, utilization, cost, scheduling, and operational telemetry. Build shared libraries, workflow and DAG or equivalent experience abstractions to evolve the data platform. Develop deployment tooling, data

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Senior Software Engineer (Federal) Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The Okta Identity Governance Team Okta Identity Governance (OIG) is Okta's Identity Governance and Administration solution, responsible for some of the most critical and visible workflows in enterprise identity: how people request access, how approvers grant it, how entitlements are enforced, and how organizations prove to auditors that only the right people have the right access. OIG is the leading contributor to Okta's new product bookings, and it runs inside some of the largest enterprises in the world — the kind of accounts where a single tenant carries hundreds of thousands of identities across thousands of applications. OIG currently supports high-compliance public sector workloads and plans to expand our footprint to support the most secure, highly classified environments in government. The Senior Software Engineer (Federal) Opportunity As a Senior Fullstack Engineer on the OIG (Federal) team, your mission

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a Staff Hardware Engineer to provide advanced operational, diagnostic, and engineering support for Graphcore’s Arm-based hardware platforms across lab and data center environments. This role focuses on supporting hardware bring-up, validation, and troubleshooting of complex AI compute platforms, including server blades, racks, and rack-scale infrastructure. The successful candidate will collaborate closely with engineering, platform, and data center teams to ensure the reliability and performance of next-generation AI systems. The Team The Systems Engineering and Hardware Engineering teams are responsible for enabling the bring-up, validation, and operational reliability of Graphcore’s AI infrastructure platforms. The team works closely with server engineering, firmware teams, platform architects, and data center operations to support the development, testing, and deployment of next-generation AI compute systems. This collaborative environment enables rapid problem-solving and continuous improvement of Graphcore’s hardware platforms from early development through production deployment.

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Senior Software Engineer — Cortex Training The Snowflake ML Platform team's mission is to let customers run their most demanding ML/AI workloads inside Snowflake. Cortex Training is our LLM post-training platform: it turns scarce, expensive GPU capacity into a simple, composable service, so customers can adapt open-weight foundation models to their own business problems while we handle the hard distributed-systems parts, including scheduling, orchestration, multi-node training and inference, fault tolerance, and throughput. The platform already runs post-training at scale. Under the hood, it decouples GPU computation from the training loop and exposes it as primitive APIs that compose into everything from SFT to full RL workflows. You'll work alongside a team that ships fast & sweats reliability and the researchers behind DeepSpeed. We're looking for an engineer who thrives in the ML infrastructure layer and brings a solid understanding of LLMs and post-training to help us scale and grow it. YOU WILL: Design and build across the full stack — from the public training APIs and SDK through the control plane to the GPU data plane. Scale the distributed systems that make GPU compute serverless — multi-tenant scheduling, placement, and capacity-aware routing across regional G

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. The Data team within Plaid’s Fraud organization builds the machine learning systems that power Plaid’s fraud detection products, leveraging Plaid’s unique network data to identify and stop fraud before it happens. The team owns the full ML lifecycle—from feature pipelines and model training to production serving and monitoring—building reliable, scalable systems that deliver high-quality fraud detection as we grow to support hundreds of customers. As a Senior Machine Learning Engineer, you will own the development of high-performance feature computation and online inference pipelines that power production machine learning systems at scale. You’ll build robust observability, monitoring, and automated debugging capabilities, while leveraging AI-assisted tools to investigate complex system behavior and maintain high reliability. You’ll partner closely with ML Infrastructure, Data Science, and Product teams to execute critical technical initiatives and deliver scalable, high-impact ML solutions. Responsibilities: Build and scale machine learning systems that power a rapidly growing fraud detection product in a fast-paced environment. Solve complex technical challenges at the intersect

Who we are About Stripe Stripe, LLC. is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. What you’ll do Responsibilities Lead the technical design and architecture of major platform initiatives, author design documents and build consensus across engineering teams. Define technical roadmaps for complex, multi-quarter projects that span multiple teams. Make critical architectural decisions for company documentation infrastructure, balancing scalability, reliability, and developer experience. Evaluate and set direction for integrating emerging technologies, including AI/LLM capabilities, into company documentation platforms and authoring tools. Establish and evolve engineering standards, best practices and technical guidelines for the team and broader organization. Partner with engineering teams across the company to understand documentation needs and design integrated solutions. Design, build and maintain scalable, reliable and performant services and systems. Contribute high-quality code across the full stack and navigate codebases with different languages and tools. Debug and resolve complex production issues and improve system reliability. Take ownership of system health and incident response. Who you are Minimum requirements Must have a Bachelor's degree or foreign equivalent in Computer Science, Software Engineering, Engineering, or a related field, plus four (4) years of experience in Software Engineering. Must have four (4) years of experience in each of the following: - Working in a full stack environment with a foc

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Senior Solutions Engineer (Enterprise Pre-Sales) Secure Every Identity, from Human to AI Agent About the Role At Okta, we believe that identity is the foundation of security and digital transformation. As a Senior Solutions Engineer, you will be the trusted technical advisor to our largest, most complex enterprise customers and a critical driver of our sales organization. We are looking for a highly strategic Pre-Sales professional whose consultative expertise, emotional intelligence, and enterprise sales acumen are their defining strengths. While technical agility is required, your primary focus will be owning the technical sales cycle by anchoring technical features to positive business outcomes. You will partner closely with Enterprise Account Executives to uncover top-of-mind business challenges—specifically around mitigating risk, reducing costs, and driving operational efficiency. By establishing value-based conversations, you will prove how Okta’s independent, neutral, and end-to-end identity platform can transform their architecture and secure the "Tech Win" on large-scale deals. What You'll Be Doing Master the Discovery Process: Leverage exceptional active listening to dig deep into customer pain points. You will uncover the 'why' behind the initiative, focusing on how Okta's vast pre-built integrations and scalable architecture can solve their most complex, diverse environmental challenges. Navigate Complex Organizations: Translate highly technica

The NVIDIA DGXC Data Services team builds cloud-native systems, frameworks, and services for managing data across hybrid and multi-cloud infrastructure. We are building the next-generation data and storage infrastructure to solve some of the hardest problems in AI: storage, access, ingestion, governance, observability, and data management for exabyte-scale, high-performance GPU-based training and inference jobs. Our work gives NVIDIA teams the foundational capabilities they need to build, train, deploy, and operate AI products at scale without reinventing critical data infrastructure for every workload. What you will be doing: Build cloud-native data and storage services for hybrid and multi-cloud infrastructure, including dataset discovery, ingestion, governance, checkpointing, observability, and low-latency access. Develop scalable cloud-native services and APIs that support exabyte-scale, high-performance GPU training and inference workflows. Work closely with product managers, internal AI teams, platform teams, and partner engineering teams to understand requirements and turn them into reliable production systems. Collaborate with SRE, operations, and support teams to improve service reliability, performance, observability, on-call readiness, and operational scale. Use modern software engineering practices, including AI-assisted and agentic development workflows, while maintaining high standards for design, testing, security, and verification. What we need to see: BS in Computer Science, Information Systems, Computer Engineering, or equivalent experience, with 5&#43; years of software engineering experience. Strong foundation in algorithms, data structures, distributed systems, and practi