Distributed Systems Engineer Data Platform Delivery Database Retrieval Jobs

About Us At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in. Available Locations:Austin, US At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code.

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

About Us At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in. Available Locations: Washington DC, Austin, NYC, San Francisco About the Dept Cloudflare’s engineers build and operate the software that helps power 25+ million Internet properties and millions of businesses around the world. Across our engineering organizations, we have opportunities for high caliber, curious and empathetic people to take on big challenges and build some of the best skills in the industry. We’re looking for talented team me

Datadog's Software Engineers with Systems depth leverage their experience with systems and tooling to build software that ensures Datadog remains reliable, performant, and secure. For this track, their Software Engineering experience may resemble the Distributed Systems track, but is typically applied in combination with their systems experience to build and run internal platforms and tools that our products are built on. These people typically have deep experience building and managing large cloud infrastructure deployments, or leading reliability efforts for orgs similar to ours, or building release machinery to allow hundreds or thousands of devs to do their jobs without stepping on each others' toes. The systems and tooling where they may have experience depth may include (but not limited to): bazel, build tooling, cassandra, CDN, chef, configuration management, container orchestration, consul, docker, elasticsearch envoy, haproxy, kafka, kubernetes, load balancing, network architecture, postgres, redis, release management, RPC frameworks, service discovery, spinnaker, terraform, zookeeper. Bonus: You’re excited about leveraging AI tools to enhance how you code, solve problems, and build – or eager to learn how 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. #LI-KM5 Datadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, Datadog offers a wide range of best in class, comprehensive and inclusive employee benefits for this role including healthcare, dental, parental planning, and mental health benefits, a 401(k) plan and match, paid time off, fitness reimbursements, and a discounted employee stock purchase plan. Th

Lead Software Engineer (C++) - Ad Tech & Distributed Systems - FreeWheel — IL - Chicago, 350 N. Orleans St 1300N. Apply via Workday.

Sr. Software Engineer - Ad Tech & Distributed Systems - FreeWheel — VA - Reston, 11951 Freedom Dr Ste 900. Apply via Workday.

About the Team: The Database Systems team specializes in high-performance distributed databases. Our team built Rockset, the real-time search, analytics, and vector database that powers all vector search and retrieval augmented generation (RAG) at OpenAI. In addition to retrieval, as an online database, Rockset powers core functionality across all of OpenAI's product lines and many critical internal use cases. About the Role : We are looking for engineers passionate about distributed systems, close-to-the-metal performance optimization (our core engine is written in C++), and building scalable database infrastructure from the ground up. As an engineer on the Database Systems team, you'll contribute to the core database engine, driving improvements across ingestion, query execution, indexing, and storage. You'll partner with teams across OpenAI to unlock new product capabilities and help scale online database reliability and throughput as usage grows by orders of magnitude. In this role you will: Design, build, and operate high-performance distributed systems Identify and resolve performance bottlenecks to scale infrastructure to the next order of magnitude Define long-term technical direction and guide system evolution Collaborate with product, engineering, and research teams to deliver scalable and reliable infrastructure Dig deep into complex production issues across the stack Contribute to incident response, postmortems, and best practices for system reliability You might thrive in this role if you: Have significant experience building, scaling, and optimizing distributed systems at scale Are curious about database internals, storage engines, or low-latency query systems Enjoy debugging challenging performance issues in complex, high-throughput systems Have experience operating production clusters at scale (e.g., Kubernetes or other orchestration systems) Think rigorously about scalability, correctness, and reliability Thrive in fast-paced environments with high

About the Role Together AI runs one of the largest GPU fleets in the world. The Infra Agent Systems team builds the software systems that power and automate that infrastructure. We develop production AI agents that diagnose hardware failures, investigate incidents, correlate signals across the fleet, and automate operational workflows. Alongside these agents, we build the platform they run on, including knowledge graphs, retrieval systems, orchestration frameworks, and developer tooling. You’ll work across two areas: Infrastructure Agent Systems — Build production AI agents that help operate our GPU fleet by diagnosing failures, investigating incidents, gathering evidence from live systems, and assisting with remediation. These agents are used every day by our infrastructure and datacenter teams through APIs, CLI, dashboards, and Slack. Core Agent Platform — Build the platform that powers these agents, including knowledge graphs, search and retrieval, orchestration, evaluation, and the tooling that enables agents to reason, act, and continuously improve. We’re working on something that hasn’t really been done before: building knowledge graphs and self-improving AI agents that understand, operate, and continuously improve large-scale AI infrastructure. This is an opportunity to work at the intersection of AI agents, distributed systems, infrastructure, and automation , solving challenging engineering problems with real production impact. There’s an enormous amount to build, learn, and shape as we define the future of autonomous infrastructure. responsible for delivering the software but also for operating and supporting it in production. Why this Role You’ll work on two hard problems at the same time: making AI agents trustworthy enough to operate production infrastructure, and building the knowledge, retrieval, and distributed systems that make those agents effective. You’ll have the opportunity to build foundational systems from the ground up, work on infrastructur

About Us At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in. Senior Systems Engineer Available Locations Austin Atlanta Denver Seattle About the Role This is a hands-on software engineering role on the Cloudflare One Appliance team. You will shape and build the Linux-based edge runtime and distributed control plane that connect customer sites to Cloudflare. As a Senior Systems Engineer, you will work across low-level systems, distributed services, and API design while providing technical leadership for majo

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 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

NVIDIA is seeking a Senior Software Engineer to help us develop distributed storage services for AI/ML. In this role you will work closely with the broader NVIDIA team to design and build a reliable, scalable, and efficient storage-as-a-service tailored to AI applications that can be deployed anywhere and scale without limitations. This service supports the whole NVIDIA critical business from graphics drivers to autonomous vehicles to deep learning frameworks. To achieve this goal, we are looking for an engineer with a deep understanding of distributed systems, outstanding design skills, and a track record in building and delivering large-scale distributed services. What you will be doing: Leading the overall architecture and design of our distributed storage service optimized for AI/ML Develop and maintain distributed, robust and scalable Go programs deployed to state of the art open-source ecosystems, including Kubernetes. Develop and maintain user-space applications, containers, Go-bindings, and CLI tools. Building features for a distributed storage service to enhance availability and reliability for large-scale deployments Engaging and collaborating with NVIDIA Research, Computing, Product teams, cross-functional teams, and external customers to deliver Cloud services. Automating distributed storage service end-to-end, including deployment, management, and monitoring What we need to see: Bachelor’s of Science in Computer Science, or related field (or equivalent experience) with 8+ years of industry experience Strong background in developing distributed systems involving Golang, Kubernetes, and Cloud Service Provider integrations Strong track record of delivering distributed services in a variety of distributed computing environments Experience in i

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. As our TT-Distributed Software Engineer, you will develop and optimize distributed software systems that power the most efficient and highest-performing AI and HPC clusters. In this role, you'll work on distributed programming across multiple nodes, utilizing systems programming, inter-node communication, and Tenstorrent’s scalable architectures to advance the state-of-the-art distributed inference and training infrastructure. 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 You Are Strong C or C++ engineer with solid foundations in systems programming, operating systems, and distributed systems principles. Enthusiastic about distributed computing, including IPC, socket programming, and cluster resource coordination. Comfortable reasoning about scalability, fault tolerance, and performance across multi-node environments. Curious and first-principles thinker who challenges conventional approaches to distributed system design. Motivated to grow into a deep technical expert in large-scale distributed AI infrastructure. What We Need Architect, implement, and optim

About the Role We are a small team of AI builders in Paytm Labs. As a Staff AI Platform Engineer, you will work across inference and agentic systems. You will contribute to Paytm's AI inference platform (Pi), serving internal teams and enterprise customers - running our own coding and domain-specific models (voice, vision, risk, fintech workflows) as well as third-party models. You will also architect and build the platform that enables autonomous AI agents to operate safely and reliably in production - the runtime, orchestration, and developer tooling for agents to reason, plan, use tools, and execute complex multi-step workflows, automating both software development and business processes. You will work at the intersection of LLMs, distributed systems, and production fintech infrastructure, helping define how inference and agentic AI are built and deployed across payments, risk, fraud, collections, support, and developer experience.

About Vercel: Vercel is the agentic infrastructure company, freeing people and agents to ship what's next. For more than a decade we've helped builders move from idea to production with speed, security, and exceptional developer experience. Now we're scaling our products for both agents and people to ship and run software, built in the open and trusted by OpenAI, PayPal, Ramp, Supreme, and millions of developers worldwide. About the Role: The Scheduled Tasks team builds the platform primitives that let applications and agents run work now, later, or for a long time. We own Vercel Workflows, Queues, and Cron: the systems developers use to build long-running, event-driven, and scheduled applications. You will join a team working at the intersection of developer experience and distributed systems. Together, we are building and scaling the products that make it straightforward for developers to coordinate background work, move messages between services, and schedule work with confidence. You will collaborate closely with engineers across Vercel to make these powerful capabilities feel simple, composable, and native to the platform. What You Will Do: Design, build, and operate platform capabilities across Workflows, Queues, and Cron. Help developers build applications and agents that coordinate background, event-driven, and scheduled work. Build APIs, SDKs, and tooling that make it easy to define, run, and manage durable work at scale. Work on the distributed-systems foundations behind scheduling, message delivery, execution, retries, and state. Partner with product, developer experience, and infrastructure teams to turn customer needs into clear, useful developer primitives. Raise the engineering bar through thoughtful design reviews, well-tested code, production ownership, and clear technical communication. Engage with developers and the open-source community to understand where background jobs, queues, and scheduling create friction—and use that feedback to improve th