Distributed Systems Engineer Data Platform Delivery Database Retrieval in United States

Distributed Systems engineers at Datadog design, implement and run in production the foundational platforms powering our applications. Your data pipelines will ingest, store, analyze and query in real-time billions of events per second from companies all over the globe. The platforms are optimized for durability, high availability, low latency, internet-scale footprint and operability. 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: Build fault-tolerant, horizontally scalable solutions running in multi-tenant environments Write in Go, Java Rust or C++, amongst other languages Use Kafka, Redis, Cassandra, Elasticsearch and other open-source components Own meaningful parts of our service, have an impact, grow with the company Who You Are: 6+ years of experience You have a BS/MS/PhD in a scientific field or equivalent experience You have significant backend programming experience in one or more languages (Go, Java, Rust, C++) You have been exposed to working on problems (high durability / low latency /…) You can get down to the low-level when needed You care about simple designs and performance You want to work in a fast, high-growth startup environment that respects its engineers and customers You have demonstrated ability to use AI coding tools in day-to-day workflows and validate, critique, and refine AI-generated output. Bonus: you’re motivated to push the boundaries of how AI can improve software engineering best practices and contribute to building AI-enabled products. This job is available in various departments within our company; to conform to US export control regulations, some of these roles may require candidates to be eligible for any required authorizations from the US government. Datadog values peo

We’re looking for a Software Engineer to architect and build backend systems that enforce data privacy and automate compliance at scale. You’ll work closely with product, infrastructure, security, and legal teams to embed privacy-by-design into our data and access layers. This is a hands-on, high-impact role for an experienced engineer who is passionate about protecting user data while enabling innovation. What You’ll Do Design, build, and operate backend services that enforce policy-driven data access, lifecycle controls, and privacy protections. Develop distributed authorization and identity-aware enforcement mechanisms integrated directly into data services and control planes. Implement auditability, policy hooks, and enforcement observability to ensure compliance is continuously verifiable. Partner with Security, Legal, and Compliance to convert privacy requirements into scalable technical designs and developer-friendly APIs. Harden data platforms and backend services through schema-level controls and data handling constraints by default. Collaborate with infrastructure teams to ensure consistent enforcement across systems while minimizing duplicated implementations. Contribute patterns, libraries, and education that elevate trustworthy data access patterns across the organization. You Might Thrive in This Role If You Have 5+ years of industry experience building and operating backend or infrastructure systems in production. Strong software engineering fundamentals , with fluency in at least one major programming language (e.g., Python, Go, Rust, C++, Java). Experience with distributed authorization, RBAC/ACL systems, encryption-based access, or policy engines. Familiarity with global privacy regulations and their architectural implications. Ability to influence and collaborate with teams across legal, compliance, product, and engineering. A bias toward practical, impactful solutions that balance privacy protections with product needs. Nice to Have Experience wi

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 Forward Deployed Infrastructure Engineers (FDIEs) build, operate, and maintain the infrastructure that powers Palantir’s platforms and production deployments. As an FDIE intern, you’ll work alongside full-time FDIEs to deploy and operate Palantir software across real production environments, automate manual processes, and develop novel solutions to infrastructure challenges using tools like Foundry and Apollo. Every day looks different — you might be debugging a distributed systems issue, building automation to replace a manual runbook, or designing infrastructure improvements that scale across multiple deployments. You’ll be treated as a full member of the team, with real ownership over the work you take on. Core Responsibilities As an FDIE intern, your responsibilities look similar to those at a small startup, with the resources, stability, and mentorship of an established tech company. You’ll work in small teams with minimal supervision and own end-to-end execution of real infrastructure projects. Your day might span discussing systems architecture with fellow engineers, debugging a production issue, building automation to eliminate a manual process, or deploying new Palantir products across production environments. FDIE interns are treated just like full-time engineers, with significant freedom and ownership over their work. Specifically, you can expect to: Deploy and operate Palantir software across production environments, including monitoring, alerting, configuration management, and upgrades Debug, improve, and optimize Palantir’s services and infra

About the Team Compute Foundations builds the software that manages OpenAI’s GPU compute infrastructure across sites, data centers, and infrastructure providers, supporting model training and inference. Our systems turn large, heterogeneous fleets of machines into dependable compute for research and products. We build Kubernetes-based control planes, controllers, services, and APIs that coordinate the lifecycle of machines and clusters. We connect global infrastructure management with the realities of bare-metal systems, giving clients consistent interfaces across differences in hardware, topology, and provider behavior. About the Role You will build distributed systems that provision, configure, and manage compute throughout its lifecycle. Your work will connect global services and Kubernetes controllers with the systems that bring machines online, update them safely, and recover them when something goes wrong. This role combines software architecture with an understanding of how machines and data centers work. You might design a lifecycle API, improve controller performance under high concurrency and provider rate limits, or trace a provisioning failure from an API through reconciliation to network boot or host configuration. You will help these systems remain reliable as the fleet expands across sites and generations of GPU hardware. We value depth in relevant systems and the ability to connect layers. You do not need to arrive as an expert in every component of the stack. In this role, you will: Design, build, and operate Kubernetes-based controllers and distributed services that coordinate infrastructure across sites, isolate failures, and scale as GPU capacity grows. Define APIs and resource models that let clients request and track lifecycle operations through consistent interfaces across hardware platforms and providers. Build provisioning and configuration services that coordinate network boot, hardware management interfaces, and the deployment of firmware,

We are seeking a highly skilled and hard-working Senior Test Developer / test engineer to join our multifaceted Enterprise Software QA team. This role offers an outstanding opportunity to leave your mark on the design, construction, optimization and testing of large-scale infrastructure for various foundational NVIDIA unified cloud services and data center offerings. If you are a dedicated engineer with strong expertise in cloud infrastructure and distributed systems and want to apply your skills with AI tools, this role could fit you perfectly. You will thrive in an exciting, innovative environment. What you'll be doing: Work with development teams on test plans for all layers of SW stack for cloud infrastructure, execution, reviews, failure analysis and assessing overall quality and risk. Work with customer PMs on software issues including technical feedback from OEMs and CSPs. Develop key benchmarks to track execution and deploy process improvements to improve efficiency Leverage AI skills to expedite the test scope, test plan, execution and automation workflows. Lead NVIDIA Cloud and Data Center bring up activities which will involve validation, reporting, working with engineering to debug issues, providing design input at times, adding coverage in different areas. Design, develop and maintain CI/CD pipelines for continuous testing in cloud environments when needed. Perform performance, scalability, and reliability testing of cloud services. Implement and maintain test environments in cloud platforms such as AWS, Azure, or Google Cloud. Supervise the infrastructure to alert on significant events, ensuring the highest level of system performance and reliability. Work with various different partner teams to ensure availability of clusters to test on and take the lead in resolve all issues. Working with tea

About the Team The Core Services organization builds and runs the mission-critical online services that product teams rely on in production. We own foundational distributed systems and platform capabilities that enable reliable execution, high-performance services, and large-scale file/data needs across our products. This team is distinct from developer infrastructure and data infrastructure—our focus is production service foundations and core runtime services. About the Role We’re hiring an Engineering Manager, Core Services to help lead teams responsible for highly reliable, high-scale distributed systems that sit on the critical path for OpenAI products. Your team will own foundational production systems that OpenAI’s product engineering teams build on. You’ll collaborate closely with product and infrastructure partners to ship reliable services quickly, and help scale systems and teams as OpenAI grows. You’ll partner closely with senior engineering leaders to scale the org, mature operations, and drive major platform initiatives. This role requires strong technical ability. You’ll be responsible for: Managing and growing a high-performing team of infrastructure engineers. Leading teams building and operating large, critical production platforms, including cluster reliability, scaling, and rollout safety. Building and operating mission-critical distributed systems with strong operational rigor (SLOs, incident response, capacity planning, reliability). Setting technical direction for platform foundations such as workflow/orchestration capabilities, large-scale file/blob/storage services, and core service foundations. Partnering with a broad set of stakeholders, including product engineering, adjacent infrastructure teams, and (where relevant) finance/cost partners. Coaching, mentoring, and developing engineers and emerging leaders. You might thrive in this role if you: Have significant experience leading teams that run mission-critical infrastructure in production

We are a global team of innovators and pioneers dedicated to shaping the future of observability. At New Relic, we build an intelligent platform that empowers companies to thrive in an AI-first world by giving them unparalleled insight into their complex systems. As we continue to expand our global footprint, we're looking for passionate people to join our mission. If you're ready to help the world's best companies optimize their digital applications, we invite you to explore a career with us! Do you get excited about complex distributed systems? Do you love data? We’re looking for an experienced technology leader to lead and grow our global engineering team and help our customers build better software by building the next generation of Application Performance Monitoring (APM) by leading our Agent teams. New Relic is committed to giving our customers valuable insights into their systems, and New Relic’s APM agents are used by tens of thousands of companies to evaluate and improve the performance of their most important business applications. Opportunity to work from a remote office may be available depending on the applicant's location. What you'll do Hands on with data analysis and technical problem solving Leverage open source tools like OpenTelemetry to acquire data Help design and build our APM agents that run in our customer environments and give engineers deep insight into application performance, and business line owners actionable intelligence on their business performance Build processes that ensure reliability, scalability, team growth and execution Work across teams to build engineering plans and execute, getting things done in a distributed, large-scale, and fast-growing environment This role requires 4+ years of experience leading people and teams 10+ years of experience in Software Engineering Proven track record of leading and scaling strong technical teams Experience handling high performing self-directed remote teams Capable of div

About the Team OpenAI’s API Multicloud team is responsible for extending OpenAI’s API platform into strategic cloud environments, starting with AWS . The team’s mission is to distribute OpenAI’s API broadly and safely by enabling key API technologies in cloud-native environments, in close partnership with Amazon and internal teams across Codex, Research, Safety Systems, and Applied. The team is focused on bringing core developer and enterprise capabilities into cloud-native environments, including cloud-hosted Codex, model customization / post-training as a service, and new stateful runtime environments for agentic workloads. This work sits at the intersection of production ML systems, developer platforms, model behavior, and large-scale infrastructure. About the Role We’re looking for a backend engineer who can quickly understand OpenAI’s models, products, and systems, then adapt first-party deployments for other cloud platforms. You’ll build backend services, APIs, SDK integrations, authentication flows, and cloud service infrastructure that let developers use OpenAI capabilities in the cloud environments where they already build. This role involves working across teams, sometimes embedded with partner product groups, to ship products quickly and across multiple platforms at the same time. It’s a strong fit for engineers who have built developer tools, especially AI-powered tools, communicate clearly across technical boundaries, and can shape architectures that support different deployment models; experience building cloud services is a strong plus. In this role, you will: Build backend and infrastructure systems that extend OpenAI’s API platform into cloud-native environments, like AWS. Design and ship cloud-contained products that allow customers to use OpenAI capabilities while keeping workloads and data within cloud environments. Help stand up cloud-hosted Codex experiences powered by the OpenAI Responses API. Build the infrastructure and runtime abstractions

About the Team OpenAI’s API Multicloud team is responsible for extending OpenAI’s API platform into strategic cloud environments, starting with AWS . The team’s mission is to distribute OpenAI’s API broadly and safely by enabling key API technologies in AWS-native environments, in close partnership with Amazon and internal teams across Codex, Research, Safety Systems, and Applied. The team is focused on bringing core developer and enterprise capabilities into cloud-native environments, including AWS-hosted Codex, model customization / post-training as a service, and new stateful runtime environments for agentic workloads. This work sits at the intersection of production ML systems, developer platforms, model behavior, and large-scale infrastructure. About the Role We’re hiring Machine Learning Engineers to build and improve the AI systems that help strategic partners adapt OpenAI models to important use cases in cloud-native environments. This role spans post-training workflows, evaluation, data pipelines, model behavior, and API/infrastructure integration. You’ll work at the boundary between partner needs and core ML systems: helping teams understand what is and isn’t working, diagnosing issues in training and evaluation workflows, and turning those learnings into improvements to the underlying platform. You should enjoy working with external technical partners, extracting the real goal from messy requests, and pushing back or reframing when the requested experiment is not the highest-leverage path. You’ll collaborate closely with Research, Applied, Safety Systems, infrastructure teams, and external technical partners to solve ambiguous model-performance problems. When you succeed, strategic partners and internal teams will be able to improve model behavior with confidence, driving measurable product improvements while the systems behind that work become more reliable, scalable, and effective over time. In this role, you will Partner with strategic customers and in

At Linear, we're building the product development system for teams and agents. AI is fundamentally changing how software gets built, and we’re shaping the tools this new era requires. Founded in 2019, Linear has become the platform of choice for more than 40,000 companies (including OpenAI, Coinbase, and Ramp) to plan, build, and ship their products. Today, our team is distributed across North America, Europe, and Australia, and we’re continuing to grow internationally. What unites us is relentless focus, fast execution, and a deep care for software craftsmanship. As a small team, we’re all generalists that work across the full stack (built in Typescript end-to-end). We’re looking for experienced engineers that thrive in an environment of autonomy and individual responsibility to help us build the future of product development. Location & work mode Linear is a remote-first company, with optional co-working offices in San Francisco, New York, and London. This role is open to candidates based in the US and Europe. You can work from anywhere within those regions. We value deep focus and async collaboration, with intentional moments to connect in person through team off-sites, optional co-working, and occasional travel. What you'll do Build new user-facing features with everything from database models to GraphQL resolvers and UI components Optimize our data synchronization stack by applying better serialization protocols Add real-time collaborative editing to our content editor Improve performance by profiling and tweaking virtualized list rendering Add analytics, monitoring, and alerts to our service so that we can better respond to operational incidents Open-source any non-trivial innovations that come out of our work on the product Redefine best-in-class software development processes so that we can build a purpose-built product. What we're looking for 5+ years of experience building customer-facing products at a high-quality software company Strong React and Typ

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 Senior Principal Network Engineer to help design, deploy, and optimize next‑generation AI data center networks. AI training and inference workloads require extremely high bandwidth, deterministic low latency, and zero‑packet‑loss networking environments. In this role, you will partner closely with the Network Architecture Lead to design and scale high‑performance computing (HPC) network fabrics supporting GPU clusters. You will work across hardware, networking, and AI application layers to ensure Graphcore’s large‑scale AI infrastructure operates at peak performance. The ideal candidate brings deep experience operating hyperscale or HPC data center networks and has expertise in high‑speed Ethernet fabrics, RDMA technologies, advanced automation, and telemetry systems. The Team The Data Center Network Engineering team designs and operates the high‑performance network fabrics that power Graphcore’s AI compute platforms. The team collaborates closely with hardware engineering, AI researchers, and infrastructure teams to build scalable networking environments optimized for distributed training and infe

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 As OpenAI continues to grow, we are looking for experienced, problem-solving engineers to ensure our systems scale. Our success depends on our ability to quickly iterate on products while also ensuring that they are performant and reliable. You will work in a deeply iterative, collaborative, fast-paced environment to bring our technology to millions of users around the world, and ensure it’s delivered with safety and reliability in mind. Successful candidates will play a crucial role in ensuring the reliability, scalability, and performance of our systems as we continue to expand. As a reliability expert, you will be at the forefront of maintaining and enhancing the stability, scalability, and performance of our rapidly evolving infrastructure. You will work closely with cross-functional teams, including software engineers, product managers, and data scientists, to build and maintain resilient systems that can handle our growing user base and workload. In this role, you will: Design and implement solutions to ensure the scalability of our infrastructure to meet rapidly increasing demands. Build and maintain the load, chaos and synthetic-testing software leveraged by development teams to make the systems they design and operate more reliable. Build and maintain automation tools to streamline repetitive tasks and improve system reliability. Build and maintain the platform for CPU, storage, GPU, and network lifecycle management to drive efficiency, accountability and dynamic optimization of our resources. Implement fault-tolerant and resilient design

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 Engineering Manager to lead a team of highly experienced engineers building the infrastructure that powers Modal's serverless GPU platform. This is a hands-on leadership role — expect to split your time between technical contribution and people management depending on what the team needs. You'll set direction, remove blockers, and build a strong engineering culture as your team tackles hard problems in distributed computing, large-scale data handling, and performance optimization. Who You Are You're an experienced engineering leader who stays close to the work and builds alongside your team when it counts. You earn trust through technical depth, not title. You communicate clearly, help strong engineers move fast without cutting corners, and stay calm and pragmatic under pressure. You care as much about how your team gets to an answer as the answ

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 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 collecti

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