Cloud Infrastructure Engineer Jobs

MongoDB’s mission is to empower innovators to create, transform, and disrupt industries by unleashing the power of software and data. We enable organizations of all sizes to easily build, scale, and run modern applications by helping them modernize legacy workloads, embrace innovation, and unleash AI. Our industry-leading developer data platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available in more than 115 regions across AWS, Google Cloud, and Microsoft Azure. Atlas allows customers to build and run applications anywhere—on premises, or across cloud providers. With offices worldwide and over 175,000 new developers signing up to use MongoDB every month, it’s no wonder that leading organizations, like Samsung and Toyota, trust MongoDB to build next-generation, AI-powered applications. Atlas Search is a multi-cloud service that allows users to execute complex full text and vector search queries using the MongoDB Query Language . Our users are free to focus on relevance and data retrieval instead of the machinery needed to search data at scale. Our team builds and maintains the instances and supporting infrastructure powering Atlas Search. This platform deploys and monitors search deployments, providing a highly scalable yet observable system for customers and engineers. The Atlas Search product is quickly gaining traction with customers and we are shipping core infrastructure components that enable this growth. This role is based in San Francisco, CA with an in-office or hybrid work model. Successful candidates will have the following qualities: 2+ years of hands-on experience designing, building, testing, and maintaining industrial-strength backend software and automation in complex codebases Experience developing distributed systems and multithreaded applications Familiarity with public cloud platforms, distributed infrastructure, and metric-based development Experience with at least one modern statically typed program

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. Role Overview As a Forward Deployed AI Engineering Manager on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, lead a team that architects specific AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a Management role that combines deep engineering and AI expertise, leading a team, and working on customer-facing problems. You'll work directly with customer engineering teams to integrate AI into their critical workflows. Key Responsibilities Customer Integration & Deployment Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows Deploy and configure AI models and agents within customer security and compliance boundaries AI Agent Development Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation Architect multi-agent systems that orchestrate between different models, tools, and data sources Implement evaluation frameworks to measure agent performance and iterate toward business objectives Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement Prompt Engineeri

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We’re looking for a customer-obsessed software engineer to come ship with us. You’ll own features like multi-node training and products like serverless reinforcement learning (RL) from conception to MVP (and from MVP to GA!). You’ll work through the stack, architecting solutions from API and UI down to our infrastructure layer. You’ll fine tune models yourself to develop an understanding of user workflows. You’ll work closely with research engineers leveraging state-of-the-art training techniques to build experiences that accelerate model development and solve for real pain points. If you’re excited to dive deep into the training, let’s talk! THE PRODUCT Take a look at what we’ve built so far: Overview of the product so far Training docs overview Story of the Training product Research we've done EXAMPLE INITIATIVES Checkpointing Pipeline: Our checkpointing pipeline starts with automated checkpointing, a feature that ensures that versions of models created during training are automatically backed up to the cloud. Users are able to then deploy checkpoints seamlessly into inference servers, providing point-and-click integrations into inference frameworks like vLLM and Baseten’s Inference Stack. This enables customers to quickly evaluate the performance of their checkpoints with real traffic. Multinode training: Multinode training enables customers to easily run training jobs across multiple compute nodes, enabling

Zscaler (NASDAQ: ZS) accelerates digital transformation so customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange platform protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Distributed across 200+ public data centers globally and thousands of private sites at the edge, the SASE-based Zero Trust Exchange is the world’s largest in-line cloud security platform. We believe the future of work is Human + AI and are building an AI-native enterprise where human potential is amplified by machine intelligence to solve the world’s hardest security challenges. Driven by deep customer obsession, we are committed to the mission, outcome, and to each other. We bring these commitments to life through three core behaviors: ownership and collaboration, trust through outcomes and impact, and a challenge culture with ongoing feedback. Ready to make an impact at the company pioneering security transformation in the AI era? Join us at Zscaler. Role We are looking for a Principal Engineer, Vulnerability & Exposure Management to join our team. This is a hybrid role, reporting to the Senior Manager, Information Security Engineering in the Product Security department. This critical role helps modernize how we discover, prioritize, and reduce security exposure across infrastructure, cloud, applications, APIs, endpoints, containers, and internet-facing assets. As an individual contributor, you will operate both strategically and technically to define the operating model, build scalable workflows, influence engineering teams, and dive deep into findings, coverage gaps, scanner limitations, and remediation paths with a strong builder mindset. What you’ll do (Role Expectations) Lead comprehensive vulnerability and exposure management initiatives across infrastructure, cloud, APIs, and containers, evolving the function from a traditional reporting role into a high-leve

Archer is an aerospace company based in San Jose, California building an all-electric vertical takeoff and landing aircraft with a mission to advance the benefits of sustainable air mobility. We are designing, manufacturing, and operating an all-electric aircraft that can carry four passengers while producing minimal noise. Our sights are set high and our problems are hard, and we believe that diversity in the workplace is what makes us smarter, drives better insights, and will ultimately lift us all to success. We are dedicated to cultivating an equitable and inclusive environment that embraces our differences, and supports and celebrates all of our team members. What You’ll Do Design, develop, and maintain scalable full-stack applications that power core products and user experiences. Build and evolve frontend user interfaces alongside robust backend services and APIs. Develop cloud-native applications using modern frameworks, languages, and cloud platforms. Lead architectural design across the stack, ensuring systems are modular, performant, secure, and maintainable. Implement and manage infrastructure-as-code to provision and operate cloud environments. Collaborate closely with product managers, designers, and other engineers to define requirements and deliver end-to-end solutions. Own the full software development lifecycle—from design and implementation to deployment, monitoring, and maintenance. Conduct code reviews, promote engineering best practices, and mentor fellow engineers. Monitor application performance and reliability across frontend and backend systems, and troubleshoot production issues with effective debugging and root cause analysis. What You Need Bachelor’s, Master’s, or PhD in Computer Science or a related technical field, or equivalent practical experience. 7+ years of professional software engineering experience, with meaningful full-stack development experience. Strong proficiency in at least one backend language (e.g., Python, Java, Go) an

P-995 About the Team At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. Ingesting data into the Lakehouse is a strategic area of investment for Databricks and a key enabler for Data and AI workflows. Lakeflow Connect is looking to solve this problem by providing ready-to-use, point-and-click connectors for a wide variety of sources, including enterprise applications (like Salesforce, Workday, ServiceNow, SharePoint), databases (e.g., SQL Server), cloud storage, message queues, and local files. In addition to being an important part of Lakeflow and Data Engineering, Connect is also a key platform capability. Every surface in Databricks (Dashboards, Notebooks, SQL, AI) requires ingestion capabilities and the lead for this role will need to work closely with other products to embed Connect into these surfaces. We are looking for a senior leader to run our Connect organization in India. This is a great opportunity to lead a key strategic initiative for Databricks. The ideal candidate would have experience leading teams that build Data infrastructure as well as interest/experience in running product centric organizations. We would also look for the ability to collaborate effectively across time zones as well organizational boundaries. The impact you will have: Solve real business needs at a large scale by applying your software engineering Ensure consistent delivery against milestones and strong alignment with the field working "two-in-a-box" with product leadership Evolve organizational structure to align with long term initiatives, build strong "5 ingredient" teams with good comms architecture Manage technical debt, including long term technical architecture decisions and balance product roadmap Leading and participating in technical, product, and design discussions Building, managing, and ope

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The Security Engineering team's mission is to safeguard our AI systems and maintain the trust of our users and society at large. Whether we're developing critical security infrastructure, building secure development practices, or partnering with our research and product teams, we are committed to operating as a world-class security organization and keeping the safety and trust of our users at the forefront of everything we do. Responsibilities: Build security for large-scale AI clusters across multiple clouds and bare-metal data centers, including IAM, network segmentation and encryption controls Design and implement network security controls: default-deny ingress and egress, segmentation between research, training and production environments, private connectivity across clouds and data centers, cloud firewall policy and mTLS with service identity Ship these controls as secure defaults using infrastructure as code and GitOps workflows, so new clusters, VPCs and data center links inherit the right boundaries Build visibility into network traffic and boundary drift, with detection for exfiltration paths and automated remediation where it is safe to do so Design secure-by-design development workflows and CI/CD pipelines across our services, with expertise in Kubernetes security, container orchestration and identity management Threat model and assess risk for complex multi cloud and networked environments, and join infrastructure networking, cluster and data center teams at design time so topology, routing and firewall decisions carry our security requirements from day one Mentor engineers and contribute to hiring and growt

The Fleet team at OpenAI supports the computing environment that powers our cutting-edge research and product development. We oversee large-scale systems that span data centers, GPUs, networking, and more, ensuring high availability, performance, and efficiency. Our work enables OpenAI’s models to operate seamlessly at scale, supporting both internal research and external products like ChatGPT. We prioritize safety, reliability, and responsible AI deployment over unchecked growth. About the Role The Software Engineer, Operating Systems & Orchestration will focus on building systems to manage hardware, configurations, vendors, and the people interacting with our infrastructure. You will design and develop solutions that integrate individual nodes and servers into unified clusters, directly contributing to advancing AI research by streamlining the overall research user experience. 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 and build systems to manage both cloud and bare-metal fleets at scale. Develop tools that integrate low-level hardware metrics with high-level job scheduling and cluster management algorithms. Leverage LLMs to coordinate vendor operations and optimize infrastructure workflows. Automate infrastructure processes, reducing repetitive toil and improving system reliability. Collaborate with hardware, infrastructure, and research teams to ensure seamless integration across the stack. Continuously improve tools, automation, processes, and documentation to enhance operational efficiency. You might thrive in this role if you: Have strong software engineering skills with experience in large-scale infrastructure environments. Possess broad knowledge of cluster-level systems (e.g., Kubernetes, CI/CD pipelines, Terraform, cloud providers). Have deep expertise in server-level systems (e.g., systems, containerization, Chef,

P-1107 At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high-value challenges that are central to their missions. Customers trust Databricks with their most valuable data, and Trust & Safety has the mission to build the most trusted Data and AI platform in the world. Identity and Access Management (IAM) is at the heart of this mission, ensuring that the right users and services have the right access at the right time. We are looking for an Engineering Manager to lead our IAM team and define the strategy for how authentication, authorization, and identity services are built and scaled across our platform. You will lead a team owning foundational services that must be highly reliable, secure, and fast under extreme load. The impact you will have: Define and drive the strategy for IAM systems, including authentication and access control. Build and scale a high-performing engineering team focused on authentication, authorization, and identity management at cloud scale. Provide technical oversight on architecture and design for IAM components that can operate at massive scale, with high requirements for reliability, security, and performance. Partner with engineering and product leaders across Databricks to embed secure, scalable identity solutions into every aspect of our product. Ensure regulatory compliance and alignment with industry best practices for IAM, helping customers meet their own governance, privacy, and security needs. Attract and grow top engineering talent, building a team culture that emphasizes innovation, collaboration, and customer trust. What we look for: 9+ years of professional experience in software engineering, with 2+ years of engineering leadership experience in a fast paced, dynamic environment. Experience buildin

RDQ127R9 At Databricks, we are obsessed with Data + AI to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high-value challenges that are central to their missions. Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, CA to a global organization with over 6500 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest-growing SaaS companies in the world. The Money team's mission at Databricks is to maximize the value that our customers derive from their investments in data projects. We accomplish this through innovative commercialization strategies and cutting-edge engineering. Our team ensures timely, accurate, and customizable billing and usage data, alongside budgeting, forecasting, and cost optimization tools. We provide a seamless and consistent billing experience for all our customers, whether they are large enterprises or individual developers, across different pricing plans and cloud providers (AWS, GCP & Azure). As a Sr. Staff Software Engineer on the Money team, you will be closely involved in the entire billing process, including usage ingestion, metering, pricing, credits, promotions, payments, usage reporting, and cost center and budgeting. Your role is crucial in democratizing data by bringing Databricks products to market. By collaborating with marketing, product teams, commercialization experts, data scientists, IT, and customer support, you will standardize billing experiences across major cloud providers, offering our customers a unified "sky computation" experience. This role involves utilizing the latest Databricks products and tools within the ecosystem. The impact you will have: Design and manage the Money system

A World-Changing Company Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more. The Role Apollo is Palantir’s autonomous software management and deployment platform. It enables seamless, continuous delivery of mission-critical software (Foundry, Gotham, AIP) across a vast range of environments: on-prem, public cloud, disconnected (air-gapped) networks, and highly regulated settings (including IL-5 and FedRAMP). As a Software Engineer on the Apollo team, you’ll build and operate a large-scale distributed system to allow the remote operation and maintenance of Kubernetes clusters. Our mission is to extract the entire state of a cluster into a portable, high-performance artifact within minutes, enabling full and almost instant cluster reconstruction from the ground up—all while pushing the limits of speed, reliability, and scale. You’ll design and implement backup and restore solutions for Kubernetes, leveraging proprietary compression infrastructure tailored to Palantir’s unique deployment models. You’ll also build and optimize our container artifact store, which is based on the OCI (Open Container Initiative) distribution spec—the industry standard for storing and distributing container images and artifacts. You’ll own the backbone of every environment Apollo supports, from hyperscalers to Army trucks. If you’re excited by challenges at the intersection of container technologies like OCI and docker, storage, and distributed systems, you’ll find opportunities here to dive deep into storage formats and low-level optimizations, where milliseconds matter. As we increasingly automate cluster creation and management on diverse hardware, you’ll play a key role in scaling Palantir’s presence at the edge and solving tough distributed systems proble

A World-Changing Company Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more. The Role Apollo is Palantir’s autonomous software management and deployment platform. It enables seamless, continuous delivery of mission-critical software (Foundry, Gotham, AIP) across a vast range of environments: on-prem, public cloud, disconnected (air-gapped) networks, and highly regulated settings (including IL-5 and FedRAMP). As a Software Engineer on the Apollo team, you’ll build and operate a large-scale distributed system to allow the remote operation and maintenance of Kubernetes clusters. Our mission is to extract the entire state of a cluster into a portable, high-performance artifact within minutes, enabling full and almost instant cluster reconstruction from the ground up—all while pushing the limits of speed, reliability, and scale. You’ll design and implement backup and restore solutions for Kubernetes, leveraging proprietary compression infrastructure tailored to Palantir’s unique deployment models. You’ll also build and optimize our container artifact store, which is based on the OCI (Open Container Initiative) distribution spec—the industry standard for storing and distributing container images and artifacts. You’ll own the backbone of every environment Apollo supports, from hyperscalers to Army trucks. If you’re excited by challenges at the intersection of container technologies like OCI and docker, storage, and distributed systems, you’ll find opportunities here to dive deep into storage formats and low-level optimizations, where milliseconds matter. As we increasingly automate cluster creation and management on diverse hardware, you’ll play a key role in scaling Palantir’s presence at the edge and solving tough distributed systems proble

About the Team Join the engineering teams that bring OpenAI’s ideas safely to the world! The Applied Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. 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 We’re seeking Software Engineers who can solve complex, high-impact problems across our stack. In this role, you’ll join a nimble team driving the deployment of OpenAI’s technology into new environments and infrastructure that power critical missions in the public sector. You’ll work cross-functionally with product, security, and compliance teams to build the functionality needed to deliver a scalable, reliable platform. You’ll also partner directly with customers to design and build new products and features that create real-world impact. From launching net-new capabilities to optimizing how we serve inference in unique, high-stakes environments, this role offers both breadth and technical depth—giving you the opportunity to shape the future of OpenAI’s technology where it matters most. This role is based in Washington D.C., San Francisco, CA or Seattle, WA. Occasional travel to customer sites is required for this role. In this role, you will: Own the development of new customer-facing ChatGPT and OpenAI API features end-to-end, both on-premises and in the cloud, for our public sector customers. Partner and directly embed with teams across the business, including engineering, security, and compliance, to enable our products to work within the unique constraints of new environments. Talk to users to understand their problems and design solutions to address them Work with the research team to get relevant feedback and iterate on their latest models, developing solutions specific for public sector customers at both the model & data

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Team The Security Engineering team protects Anthropic's AI systems and maintains the trust of our users and society. We define the authentication architecture for our training infrastructure, design the cryptographic foundations that protect model weights and training data, and drive the developer security program that shapes how engineers build and ship software. The team works across several areas that collaborate closely: identity and secrets management, developer security and supply chain, infrastructure security, and secure frameworks. You will support one of these areas while contributing across others, with your focus shaped by your strengths and the team's priorities. Responsibilities: Build and maintain identity and secrets management systems, including credential issuance, rotation, and workload authentication across our multi-cloud environments Contribute to cluster security controls including RBAC policies, namespace isolation, workload identity, and pod security Implement and maintain cloud security controls including IAM, network segmentation, VPC architecture, and encryption across our multi-cloud and on-prem environments Design and implement secure development frameworks and libraries that make secure coding the path of least resistance for our engineering teams, including service to service authentication, serialization libraries, and tool proxies. Harden CI/CD pipelines against supply chain attacks through isolated build environments, signed attestations, dependency verification, and automated policy enforcement Identify and remediate security gaps through code review, threat modeling, and hands-on debuggin

RDQ426R193 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Search plays a foundational role in this mission. Whether through keyword-based retrieval, semantic similarity via vector embeddings, or hybrid approaches that combine both, our Search technologies help customers find, discover, and understand information across massive, complex datasets. These capabilities power everything from Retrieval Augmented Generation (RAG), AI assistants, and recommendation systems to enterprise knowledge management, in-product search, and data exploration. As a Senior Engineering Manager for Search, you’ll play a critical role in building and scaling our next-generation Search product — spanning Vector Search, Keyword Search, and Search Quality. You’ll drive the design and evolution of a highly-performant, cost-efficient, and developer-friendly Search stack that enables customers to build AI applications with accuracy, speed, and scale. Beyond hands-on contributions, you’ll help define the long-term vision, mentor senior engineers, collaborate across teams, and lead strategic efforts that expand the technical and business impact of Search at Databricks. Check out our recent blog post: Decoupled by Design: Billion-Scale AI Search The impact you will have: Lead a team of talented software engineers to design, build, and operate the next-generation cloud-native Search services. Drive innovation across Vector Search, Keyword Search, and Hybrid Search capabilities to improve relevance, latency, and cost efficiency. Build a strong partnership with product and research teams to define the roadmap for Search Quality, including ranking models and evaluation frameworks. Mana