Distributed Systems Engineer 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

About the Team The Platform Systems team at OpenAI operates at the intersection of cutting-edge AI and large-scale distributed systems. We build the engineering and research infrastructure required to train OpenAI’s flagship models on some of the world’s largest, custom-built supercomputers. Our team develops core model training software and works deep in the stack - spanning collective communication, compute efficiency, parallelism strategies, fault tolerance, failure detection, and observability. The systems we build are foundational to OpenAI’s research velocity, enabling reliable, efficient training at frontier scale. We collaborate closely with researchers across the organization, continuously incorporating learnings from across OpenAI into the evolution of our training platform. About the Role As a Software Engineer, Platform Systems, you will design and build distributed systems that provide visibility into large-scale training workloads and help operate them reliably at scale. You’ll work on failure detection, tracing, and observability systems that identify slow or faulty nodes, surface performance bottlenecks, and help engineers understand and optimize massive distributed training jobs. This infrastructure is critical to operating OpenAI’s training stack and is actively evolving to support new use cases and increasingly complex workloads. This role sits at the core of our training infrastructure, blending systems engineering, performance analysis, and large-scale debugging. In This Role, You Will Design and build distributed failure detection, tracing, and profiling systems for large-scale AI training jobs Develop tooling to identify slow, faulty, or misbehaving nodes and provide actionable visibility into system behavior Improve observability, reliability, and performance across OpenAI’s training platform Debug and resolve issues in complex, high-throughput distributed systems Collaborate with systems, infrastructure, and research teams to evolve platform

About the Team The Recursive Self-Improvement (RSI) team works across research, engineering, product, and infrastructure to build AI systems that accelerate and ultimately conduct high-quality research at OpenAI. We work to automate real research workflows and improve research productivity by building systems and feedback loops, designing evaluations, and training models to develop missing capabilities. Our work spans the full lifecycle of model training, evaluation, and deployment to help researchers move faster and tackle increasingly ambitious problems. About the Role We’re hiring research scientists , research engineers , and AI systems engineers to work on automating research at OpenAI. This role is based in San Francisco, CA. In this role, you will: Design evaluations for research judgment, hypothesis generation and testing, and long-horizon experiment execution. Turn real research workflows and model failures into data and evaluation flywheels. Improve model research capabilities through agent harnesses, synthetic data, RL environments, and model training. Build and maintain safe, reliable integrations between our models and OpenAI’s research infrastructure. Develop research agents, experiment-orchestration systems, and sandboxed runtimes that support real research workflows. Create metrics and economic models to understand RSI’s current and future effects on research productivity, model capabilities, and the safety of internal deployments. This is a high-ownership role for researchers and engineers who thrive in ambiguity, move fluidly between research and implementation, and turn emerging opportunities into rigorous, reliable, scalable results. You might thrive in this role if you: Have research or engineering experience across LLM training, model evaluations, agent systems, synthetic data, research infrastructure, or large-scale distributed systems. Are a strong generalist who can move between open-ended research and practical implementation, turning ambig

About the Team pAGI Infra team builds and operates the systems that make large-scale model training and evaluation reliable, efficient, and easy to run. Our work spans distributed training infrastructure, inference and grading platforms, compute scheduling, and research tooling. We partner closely with researchers and engineering teams to turn new research needs into dependable infrastructure, improve GPU efficiency, and shorten the path from an experiment to a validated model. About the Role We’re looking for an AI Systems Engineer to help scale the infrastructure behind our training and evaluation workflows. You’ll own projects from identifying bottlenecks and designing solutions through deployment and operation. The work combines distributed systems engineering, performance optimization, and close collaboration with researchers. You might build a shared grading service, improve resource allocation across workloads, or bring a new training stack into production — directly improving how quickly and reliably research moves forward. In this role, you will: Build and operate infrastructure for large-scale training and evaluation, improving reliability, throughput, and resource efficiency. Develop shared inference and grading platforms with automated capacity management, health monitoring, and visibility into performance. Improve compute scheduling and resource allocation to reduce idle GPU time and help workloads recover quickly from failures. Diagnose bottlenecks across training, inference, and orchestration, and work across teams to improve end-to-end performance. Build self-service tools, automated validation, and observability that help researchers launch experiments, diagnose issues, and compare results with less manual intervention. You might thrive in this role if you: Are excited about the potential of personal AGI and want to build the infrastructure that enables it. Have strong software engineering fundamentals and experience building or operating large-scal

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. Build Core Data Engineering Primitives at Cloud Scale Data pipelines are foundational infrastructure — when they're fast, correct, and maintainable, customers build on them with confidence. If you've spent the bulk of your career building large-scale data infrastructure — designing streaming or transformation primitives, reasoning hard about consistency and fault tolerance, and owning the systems that run under millions of customer workloads — this role might be for you. You'll be working on the streaming and transformation layer at Snowflake: the constructs that define how customers move, shape, and maintain data. AI has a real presence in this work — in how customers use these pipelines and in how we think about building them — but the core job is hard distributed systems engineering, and that's what we're hiring for. About the Team We build the core data engineering primitives that power Snowflake's streaming and transformation capabilities. From the constructs customers use to define real-time pipelines to the execution fabric that makes those pipelines reliable and cost-efficient at cloud scale, our team owns the full stack of declarative data engineering. We're a small, high-ownership team operating close to the product — which means your decisions ship, your architec

About the Team We’re hiring Software Engineers to join our broader Infrastructure organization, which supports multiple high-impact teams. Depending on your interests and experience, you could work on one of several focus areas—including Core Distributed Systems, Reliability Engineering, Observability, Developer Productivity or Cloud Infrastructure. About the Role All teams are deeply collaborative, work on mission-critical services, and are responsible for building distributed, scalable infrastructure to bring OpenAI’s technology to the world through products like ChatGPT and the OpenAI API. You’ll work closely with stakeholders to understand infrastructure, data and compute needs, setting the technical strategy that supports cutting-edge research and product development. This is a critical role for someone who is passionate about solving complex engineering problems at scale, ensuring their performance, scalability and reliability Team Focus Areas Distributed Systems: Owning and building important, highly scalable, available, performant, and reliable distributed systems (and their building blocks) to power the entire stack at OpenAI Systems Engineering: Work across layers of the stack—debugging system bottlenecks, evolving core infrastructure, and solving novel problems in performance and scalability. Reliability Engineering: Build scalable, fault-tolerant systems and lead efforts around service health, incident response, and resilience. Observability: Design and maintain observability tooling (metrics, logs, tracing) to give teams visibility into production systems at scale. Developer Productivity: Create tools, environments, and workflows that help engineers ship high-quality software faster and more safely. Cloud Infrastructure: Own the cloud-native infrastructure (compute, networking, storage) that underpins all services and research workloads. Databases: Building high performance, distributed database systems that power all of OpenAI's product stack. In this

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the role: We are seeking talented distributed systems engineers who are passionate about building innovative solutions for application deployment. Your mission will be to enhance the capabilities of Replit Infrastructure, optimize performance across global regions, and drive efficiency while delivering an exceptional user experience. If you have a strong foundation in software development, a deep understanding of cloud technologies, and a track record of delivering high-quality code, we want to hear from you. In this role you will: Expand Replit's cloud infrastructure offerings: Launch new cloud products to be used by Replit Agent to build complex apps. Collaborate with cross-functional teams to design and implement these features, empowering developers with a comprehensive suite of tools to build and deploy their applications efficiently. Enhance reliability and scalability: Identify bottlenecks, optimize critical paths, and implement robust monitoring and alerting systems. Work closely with the SRE team to ensure high availability and minimal downtime. Enable our customers to seamlessly scale their applications to meet the demands of their growing user base. Improve utilization of cloud infrastructure: Analyze our infrastructure costs and identify opportunities for optimization. Implement strategies to reduce cloud expenses without compromising performance or reliability. This could involve techniques such as resource provisioning, auto-scaling, cost-aware scheduling, and data lifecycle management. Your efforts will directly contribute to the financial efficiency of our cloud services. Required skills and experience: Distributed systems: Track record of working with platform-as-a-service, distributed storage, o

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is building the world’s fastest, most efficient AI compute clusters. TT-Fabric is the high-performance nervous system of this platform: the low-level networking layer that lets thousands of RISC-V and AI processors snap together into a single, massively parallel distributed supercomputer. If you love squeezing nanoseconds out of hot paths, designing protocols that move data at absurd scale, and turning messy hardware constraints into elegant distributed systems, this is an opportunity to shape the fabric that future AI models will run on This role is hybrid based out of Santa Clara, CA; Austin, TX; or Toronto, ON. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who We Are Strong systems engineer with deep C or C++ experience and comfort working in low-level or bare-metal environments. Passionate about hardware-software interaction, performance tuning, and eliminating inefficiencies at the protocol level. Curious about networking, synchronization, and communication across large clusters. Comfortable reasoning from first principles and challenging industry conventions. Motivated by building infrastructure that directly impacts large-scale

NVIDIA is hiring an NCX Senior Engineer who is passionate about NVIDIA Cloud Partner (NCP) infrastructure operations to join our DSX team. This role involves working closely with strategic NVIDIA Cloud Partners to build and improve the operational capabilities essential for running large-scale NVIDIA accelerated infrastructure reliably in production. Your role involves guiding partners beyond the initial cluster deployment and validation phase into advanced Day 2 operations. These operations cover ongoing infrastructure health, observability, lifecycle management, quick remediation, performance validation, and operational readiness. You will engage directly with partner engineering and operations teams to develop consistent approaches that support NVIDIA workloads and the broader external customer environments of the partners. This is a highly technical, hands-on role at the intersection of NVIDIA accelerated computing, cloud infrastructure, distributed systems, and production operations. What you'll be doing: Lead NCP Day 2 operational readiness efforts. Collaborate directly with NVIDIA Cloud Partners to set up the systems, procedures, automation, and operational methods necessary to consistently manage NVIDIA accelerated infrastructure following initial deployment and activation. Build continuous infrastructure validation. Develop and implement methods to continuously validate GPU, CPU, storage, and network health. Do this across large-scale AI clusters to identify degraded infrastructure before it impacts critical training or inference workloads. Establish observability and operational telemetry. Help NCPs implement comprehensive telemetry, monitoring, alerting, dashboards, and operational signals across compute, GPU, InfiniBand/RoCE networking, storage, Kubernetes, and AI workloads. Devel

About the Team API Frontiers turns OpenAI’s frontier models into production APIs that developers can use to build reliable products and agents. We own the core path connecting models to developers through the Responses API, with a focus on safety, reliability, and speed. Working closely with Research, Safety, Codex, and other API teams, we bring new model capabilities into production and improve them through developer feedback. About the Role We are looking for a backend software engineer to build and operate the services behind the Responses API. You will shape API behavior, bring new capabilities from research into production, and make long-running agent workflows dependable and fast. The work combines distributed systems engineering with product judgment: designing useful developer interfaces, managing staged rollouts, and following production issues through to durable fixes. In this role, you will: Design, build, and operate APIs and backend services that bring frontier model capabilities to developers. Partner with Research, Safety, Codex, and API teams to define API behavior and deliver safe, staged launches. Build API capabilities for agent workflows, including task delegation, context sharing, and parallel execution. Strengthen long-running request reliability across timeouts, cancellation, streaming, and background execution. Improve request-processing performance and tail latency through profiling, efficient systems code, and persistent connections. Turn developer feedback and production failures into better observability, diagnostics, and lasting product improvements. Your background might look something like: 5+ years of experience building and operating backend services or developer-facing APIs in production. Strong software engineering fundamentals, with practical knowledge of distributed systems, concurrency, and asynchronous execution. Ability to diagnose production failures and performance bottlenecks using observability data and profiling. Product

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. The Data Access team within Infra / Storage builds EaaS (Entities-as-a-Service), Roblox’s large-scale managed OLTP access and management platform powering tens of millions of QPS across thousands of services. EaaS abstracts the complexity of distributed databases and caching systems behind a consistent and productive developer experience, enabling teams across Roblox to safely build and operate stateful systems at massive scale without requiring deep database expertise. The team operates at the intersection of distributed systems engineering, reliability engineering, and platform architecture — solving hard infrastructure problems that directly impact Roblox-wide scale and stability. As a Senior Software Engineer you will work on some of Roblox’s hardest backend infrastructure challenges around scalability, reliability, workload governance, adaptive flow control, and distributed systems. You Will Build and evolve EaaS, Roblox’s managed OLTP access platform powering tens of millions of QPS across hundreds of services. Design infrastructure that abstracts distributed databases and caching systems behind a consistent, safe, and highly productive developer experience. Drive reliability and scal

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. As an Early Career Software Engineer at Roblox, your story begins with supportive mentorship and immediate, global impact. You’ll work alongside seasoned engineers and curious experts, designing, coding, and deploying real features that reach millions of people globally. By the end of your first year, you’ll have directly influenced the future of our platform and the experience of our global community with millions of daily active users. You Will: Join a community of curious, supportive engineers, actively engaging in architectural discussions and system design. Investigate and experiment with cutting-edge technologies, like machine learning frameworks and large language models (LLMs), to solve complex technical challenges and improve our engineering systems. Design, code, and test innovative features, navigating the full development lifecycle from initial design to production deployment. Partner closely with cross-functional teams, including Design, Product, Data, QA, and DevOps, to deliver cohesive products and features. Support the continuous evolution of our distributed systems, operating at our massive scale of 2 trillion analytics events a day. Engage in our team mat

About the Role We are seeking a Cloud Infrastructure Engineer to help design and evolve the platforms that power OpenAI’s products. In this role, you will be a hands-on technical leader, driving the architecture, scalability, reliability, and security of critical infrastructure systems. You will help define how we build and operate infrastructure at the next order of magnitude, while influencing technical direction across teams. This role is both deeply technical and highly strategic, requiring strong ownership, sound judgment, and the ability to partner effectively across engineering, product, and research organizations. In this role, you will: Design and build scalable, reliable, and secure infrastructure platforms that power OpenAI products Evolve cloud infrastructure abstractions that enable rapid product development across teams Architect systems to support significant growth, performance, and operational complexity Improve server orchestration, networking, distributed systems reliability, and infrastructure security posture Influence technical direction and infrastructure strategy across multiple teams Partner closely with product, research, and engineering teams to align infrastructure with evolving needs Own operational excellence, including participation in on-call rotations, incident response, and production readiness Mentor engineers and raise the overall technical bar of the organization Contribute to a culture of high ownership, low ego, and thoughtful collaboration You might thrive in this role if you: 8+ years of experience building and operating large-scale infrastructure systems Deep expertise in Kubernetes and container orchestration at scale Strong experience designing cloud abstractions and platform infrastructure (AWS, GCP, Azure, or similar) Proven track record of leading complex technical initiatives across teams Experience operating highly reliable, secure, and scalable distributed systems Security engineering experience or security backgroun

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. As a Software Engineer Intern at Roblox, your 12-week journey is designed around accelerated learning and tangible global impact. With the support of a dedicated mentor, you’ll apply your knowledge to production-scale reality as you take end-to-end ownership of a project tackling some of the hardest technical challenges, including distributed systems, real-time communication, 3D co-experience, data processing, rendering, and more. You Will: Join our supportive community of engineers, receiving dedicated mentorship as you deliver live production projects. Investigate and experiment with cutting-edge technologies, such as machine learning frameworks, agentic coding tools, and large language models (LLMs), to solve complex technical challenges and improve our engineering systems. Own a project from beginning to end, from coding and testing to deploying it to production, and presenting your work to peers and leaders across the company. Partner closely with cross-functional teams, including Design, Product, Data, QA, and DevOps, to deliver cohesive products and features. Build a close community with fellow interns and full-time builders alike, while gaining a broad perspective on the compa

About the Team OpenAI’s Compute organization turns ambitious AI research into real-world capability by delivering the compute infrastructure behind our most advanced models. The team works across software, hardware, facilities, operations, and engineering disciplines to make enormous amounts of compute available, reliable, and efficient. As the demand for frontier AI grows, so does the complexity of the systems required to support it. Scaling this infrastructure means solving problems that cut across distributed systems, ML infrastructure, GPU fleets, power, cooling, networking, manufacturing, supply chain, and data center delivery. Our work is focused on expanding the compute foundation that enables OpenAI to train more capable models, including systems like GPT-5.6, and make frontier AI available to more people, products, and workflows. We’re looking for exceptional people across many disciplines to help build the next generation of AI infrastructure at a scale few organizations have attempted. About the Role We are hiring across a broad range of roles to help design, build, scale, and operate OpenAI’s compute infrastructure. Depending on your background, you may work on large-scale distributed systems, ML infrastructure, hardware systems, manufacturing, supply chain, data center development, or the physical engineering systems required to bring massive compute capacity online. You’ll work with teams across research, engineering, hardware, operations, and infrastructure to solve high-impact problems at extraordinary scale. This may include improving system reliability, accelerating deployment timelines, increasing operational efficiency, designing new infrastructure, or helping bring new compute platforms and facilities from concept to production. This is an opportunity to work on one of the most important infrastructure challenges in AI: building the compute foundation required to train and serve increasingly capable frontier models. Key Responsibilities Help bui