Software Engineer Distributed Systems Jobs

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

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

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 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

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

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

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 is building the cloud-based distributed systems software responsible for the lifecycle of search indexes including: data ingestion, index building, partitioning, performance, availability, and backup management. Our product is quickly gaining traction with customers and we are making core architectural improvements that you will contribute to. This role is based in Toronto, ON hybrid. Successful candidates will have the following qualities: 2+ years of hands-on experience designing, building, testing, and maintaining industrial-strength backend software in a complex codebase Experience developing distributed systems and cloud services Experience with at least one modern statically typed programming language, and interest in working with Java Excellent verbal and written technical communication skills and enthusiasm for collaborating closely with colleagues A growth mindset and the desire to learn quickly through taking on challenges, reflecting on outcomes, and incorporating feedback A strong sense of ownership over their work, from initial design all the way through maintaining code in production You will: Contribute to the design, implementation, and support of projects that improve the scalability of Atlas Search to make using it a seamless experience for even the largest workloads Work with a collaborative team that prioritizes sound technical decision-making and building systems that our customers love and that we are proud of as engineers Have the opportunity to lead projects and own subsystems Provide input on the team’s roadmap and help determine the architecture of our system Success measures: In 3 months you’ll have a solid high-level understanding of what our team does and how we operate.

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 is building the cloud-based distributed systems software responsible for the lifecycle of search indexes including: data ingestion, index building, partitioning, performance, availability, and backup management. Our product is quickly gaining traction with customers and we are making core architectural improvements that you will contribute to. We are looking to speak to candidates who are based in San Francisco, CA for our hybrid working model. Successful candidates will have the following qualities: 2+ years of hands-on experience designing, building, testing, and maintaining industrial-strength backend software in a complex codebase Experience developing distributed systems and multithreaded applications Experience with at least one modern statically typed programming language, and interest in working with Java Excellent verbal and written technical communication skills and enthusiasm for collaborating closely with colleagues A growth mindset and the desire to learn quickly through taking on challenges, reflecting on outcomes, and incorporating feedback A strong sense of ownership over their work, from initial design all the way through maintaining code in production You will: Contribute to the design, implementation, and support of projects that improve the scalability of Atlas Search to make using it a seamless experience for even the largest workloads Work with a collaborative team that prioritizes sound technical decision-making and building systems that our customers love and that we are proud of as engineers Have the opportunity to lead projects and own subsystems Provide input on the team’s roadmap and help determine the architecture of our system Success measures: In 3 months you’ll have a

Scale GP is Scale's enterprise Generative AI platform—APIs and infrastructure for knowledge retrieval, inference, evaluation, and intelligent automation. We power mission-critical workflows for leading enterprises, helping teams turn complex data and models into reliable, production-ready AI systems. We're building a new AI Enablement team to create the next generation of agent-powered tools that ground AI in real operational workflows. Our goal: help internal teams demystify their own workflows, then deploy agentic systems that reason over data, take action, and deliver measurable outcomes. We don't build in a vacuum. You'll use our own platform to solve real business problems internally—then selectively commercialize that same stack for customers. What we run on is what we sell. This is a 0→1 team. We're looking for a sharp, product-minded engineer who thrives in ambiguity, moves fast, and loves building systems from scratch alongside customers and cross-functional partners. You'll work closely with product, forward-deployed engineers, data scientists, and applied AI teams to turn real-world problems into scalable production solutions. If you like shipping fast, owning outcomes, and working across the stack—from polished frontends to distributed backends to LLM integrations—this role is for you. What You’ll Do Own full-stack features and projects end-to-end — from design through production deployment — within a larger product area Sample surfaces - Accounting Agents, Finance Copilots, GTM Agents, Agentic Experimentation Platforms Develop reliable backend services in Typescript/Python, work with distributed systems, data pipelines, and AI/ML infrastructure Integrate LLMs, vector databases, and agentic frameworks to power intelligent workflows Ship quickly through tight experimentation loops while maintaining high quality and reliability Adapt across the stack and learn new tools as needed to solve real problems end-to-end Ideal Experience 3+ years of full-tim

Join the MongoDB Networking & Observability team and help build the core of a distributed database! Our team focuses on creating and enhancing components which facilitate communication between distributed processes and make these processes, and their communication, easily observable. Networking Observability’s responsibilities include improving MongoDB networking, improving the efficiency of resource utilization, and building low-overhead observability features. Our team includes engineers located in New York City and fully remote engineers. We operate close to the bottom of the stack, and have a lot of influence over the availability, performance, and robustness of our open source database. Recently, we’ve improved connection handling, explored new networking architectures, and integrated OpenTelemetry to make issues easier to diagnose and connect MongoDB to modern observability tools. We are planning to further improve our networking’s stack performance, availability and scalability as well as further enhance our observability stack using open observability frameworks. Are you excited to help the MongoDB engineering team build a better database? We are! Join us today, and we can build a faster, more reliable, exceptionally observable, database system together. This role can be based out of our New York City office or remotely within the United States and Canada. Candidate Profile 3+ years of experience building distributed systems Passionate about delivering and deploying a product with cross-team stakeholders Solid computer science fundamentals, with strong competencies in data structures, algorithms, and software design/architecture Hands-on experience with building production-level code. Experience in C++ is required Interest in furthering their knowledge of networking, observability and how computer architecture and internals impact the availability of SaaS Solid verbal and written communication skills and highly motivated to collaborate with colleagues Po

Join the MongoDB Networking & Observability team and help build the core of a distributed database! Our team focuses on creating and enhancing components which facilitate communication between distributed processes and make these processes, and their communication, easily observable. Networking Observability’s responsibilities include improving MongoDB networking, improving the efficiency of resource utilization, and building low-overhead observability features. Our team includes engineers located in New York City and fully remote engineers. We operate close to the bottom of the stack, and have a lot of influence over the availability, performance, and robustness of our open source database. Recently, we’ve improved connection handling, explored new networking architectures, and integrated OpenTelemetry to make issues easier to diagnose and connect MongoDB to modern observability tools. We are planning to further improve our networking’s stack performance, availability and scalability as well as further enhance our observability stack using open observability frameworks. Are you excited to help the MongoDB engineering team build a better database? We are! Join us today, and we can build a faster, more reliable, exceptionally observable, database system together. This role will be based remotely in Canada. Candidate Profile 3+ years of experience building distributed systems Passionate about delivering and deploying a product with cross-team stakeholders Solid computer science fundamentals, with strong competencies in data structures, algorithms, and software design/architecture Hands-on experience with building production-level code. Experience in C++ is required Interest in furthering their knowledge of networking, observability and how computer architecture and internals impact the availability of SaaS Solid verbal and written communication skills and highly motivated to collaborate with colleagues Position Expectations Understand and improve the current funct

We are hiring a Senior Software Engineer to join our Server Security team. The Server Security team is a development-focused group within MongoDB's core engineering organization. Operating "close to the bottom of the stack," the team builds features that enable database users to secure their data globally. You will work on critical components including: Cryptography: Queryable Encryption , at-rest data encryption, and fundamental cryptographic principles. Identity & Access: Authentication and authorization systems, TLS, and X.509 certificate management Network Security: High-performance, low-latency networking protocols (PKI, Hashing, CRLs) System Integrity: Resilience, observability, and compliance assurance within a large-scale distributed database Our team champions a strong culture of inclusivity, diversity, and collaboration. If you want to work on a collaborative team that applies distributed systems fundamentals to deliver core features of a popular database, join us! Let’s change what’s possible for application developers, system architects, and database operators. The role As a Senior Engineer, you will apply distributed systems fundamentals to deliver core security features. You will be a leader in improving MongoDB's security posture by owning features and leading investigations into complex areas of the codebase. What you’ll do: Build and test new security features in a large, feature-rich C++ codebase Work across engineering, cloud services, and support teams to coordinate feature rollouts and changes Stand for code quality and security best practices, assisting fellow engineers in writing well-reasoned, secure code Use strong diagnostic intuition to solve thorny technical issues related to distributed systems, concurrency, and OS internals This role can be remote or hybrid anywhere in the USA or Canada. We will prioritize candidates who are already located in one of these countries. Candidate Profile We are looking for a highly technical engineer w

We are hiring a Senior Software Engineer to join our Server Security team. The Server Security team is a development-focused group within MongoDB's core engineering organization. Operating "close to the bottom of the stack," the team builds features that enable database users to secure their data globally. You will work on critical components including: Cryptography: Queryable Encryption , at-rest data encryption, and fundamental cryptographic principles. Identity & Access: Authentication and authorization systems, TLS, and X.509 certificate management Network Security: High-performance, low-latency networking protocols (PKI, Hashing, CRLs) System Integrity: Resilience, observability, and compliance assurance within a large-scale distributed database Our team champions a strong culture of inclusivity, diversity, and collaboration. If you want to work on a collaborative team that applies distributed systems fundamentals to deliver core features of a popular database, join us! Let’s change what’s possible for application developers, system architects, and database operators. The role As a Senior Engineer, you will apply distributed systems fundamentals to deliver core security features. You will be a leader in improving MongoDB's security posture by owning features and leading investigations into complex areas of the codebase. What you’ll do: Build and test new security features in a large, feature-rich C++ codebase Work across engineering, cloud services, and support teams to coordinate feature rollouts and changes Stand for code quality and security best practices, assisting fellow engineers in writing well-reasoned, secure code Use strong diagnostic intuition to solve thorny technical issues related to distributed systems, concurrency, and OS internals This role can be remote or hybrid anywhere in the USA or Canada. We will prioritize candidates who are already located in one of these countries. Candidate Profile We are looking for a highly technical engineer w