Software Engineer Distributed Systems Jobs

At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the Role Anyscale's need to detect and respond to security events across its production and corporate environments is growing as the company scales. We're looking for a Senior Detection and Response Engineer to own detection engineering and to lead incident response when it counts, coordinating the response and driving it to resolution. This is a high-ownership role with real room to shape how detection and response works at Anyscale. You will own the detection pipeline, the response runbooks, and incident response, reporting to the Head of Security and partnering with engineering. This role is based in India. In your first year, success looks like strong detection coverage across our cloud, endpoint, and runtime telemetry, a working correlation and alerting pipeline, and incident response runbooks that have been exercised in practice. What You'll Do Own and build detection coverage across cloud, endpoint, and runtime telemetry. Own a centralized correlation and alerting capability that turns telemetry into actionable detections. Own incident response: runbooks, escalation paths, and coordination during an incident, across corporate and production environments. Drive detection of anomalous activity across the environments

At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the Role Anyscale's product security needs are growing as we ship to larger and more demanding customers. We're looking for a Senior Product Security Engineer to own our secure software development lifecycle and to be engineering's partner on building security into the product. Reporting to the Head of Security, you will work in close partnership with engineering. This is a senior, high-ownership role. You will own and operate a scalable SSDL, partner with engineering on security features and secure design, review the security of existing systems and new initiatives, and own how we find, track, drive to resolution and report on vulnerabilities in what we ship. This role is based in India. In your first year, success looks like an SSDL that scales with engineering rather than gating it, security review embedded in how new initiatives ship, and accurate, on-demand vulnerability reporting backed by a working path to resolution. What You'll Do Own and operate a scalable secure software development lifecycle: threat modeling, security requirements, secure design practices, and scanning that engineering can readily adopt. Partner with engineering on security features and secure-by-design architecture, from early design through i

About Anyscale: At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the role: Anyscale is looking for a Site Reliability Engineer to join the Infrastructure team. Anyscale aims to provide the next generation of tools and infrastructure to make developing and running distributed AI applications in the cloud as easy as on your laptop. As part of the Infra team, we build the scalable, secure, and robust backbone that enables this vision. Our team is responsible for both the control plane, which orchestrates cluster management, scheduling, and user access, and the data plane, which ensures high-performance execution of distributed workloads. We are seeking a talented engineers with a strong background in control plane and data plane development, along with expertise in Kubernetes, container orchestration, and cloud-native infrastructure. You will play a crucial role in designing, implementing, and optimizing the critical infrastructure that powers Anyscale’s cloud platform. You will have the opportunity to work on open-source Ray, contribute to our infinite laptop proprietary product, and develop seamless integration between the two, while also delivering high-impact features for our customers. A snapshot of projects you may work on Design, build, and scale services that orches

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

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

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

Perplexity is looking for an Infrastructure Engineer to own and improve the backend systems behind our latency-sensitive search stack. You’ll work across high-QPS Rust and Go services, distributed retrieval systems, cloud infrastructure, observability, and deployment tooling. This role combines infrastructure expertise with software engineering. You’ll take systems from design through production operation and use AI-native tools where they meaningfully improve engineering and operational workflows Responsibilities Build and operate scalable, low-latency infrastructure for search serving and retrieval. Design and improve distributed backend systems that handle high request volumes. Debug and optimize Linux systems, containers, networking, and production services. Improve reliability through observability, capacity planning, performance profiling, and incident response. Design, deploy, and operate cloud-native systems, primarily on AWS and Kubernetes. Build internal tools and automation for development, testing, debugging, and infrastructure operations. Improve CI/CD pipelines, release processes, and production rollout safety. Contribute directly to product codebases across Rust, Go, and other systems languages. Own systems end to end, from architecture and implementation to deployment and production operation. Requirements Strong experience with cloud infrastructure, distributed systems, and automation. Deep understanding of Linux internals, performance analysis, and production debugging. Experience building or operating latency-sensitive, high-throughput backend systems. Experience with containers, orchestration, observability, and infrastructure as code. Experience building or maintaining CI/CD systems and release tooling. Fluency in at least one systems language, such as Rust, Go, C++, or Java. Comfort working across infrastructure and application-level code. Strong ownership and the ability to operate effectively in a fast-moving environment. Nice To Have Experie

We are hiring a Senior AI Engineer to build and operate production AI systems and infrastructure. In this role, you will work on AI agents, MCP servers, agent evaluation, and Temporal-based workflow frameworks. This is a hands-on engineering role for someone who can move between backend systems, AI application development, deployment, and production support. You will help build reliable services and frameworks that make AI agents usable, measurable, and dependable in production. What you’ll be doing: Build and deploy AI agents that use tools, call services, manage context, and execute multi-step tasks. Develop and maintain MCP servers and tool integrations used by internal AI systems. Build workflow infrastructure using Temporal or similar orchestration frameworks. Design and implement agent evaluation flows, test suites, quality metrics, and feedback loops. Design backend services, APIs, persistence layers, and platform components for AI applications. Work with SQL and NoSQL databases, queues, distributed systems, and cloud-native infrastructure. Build CI/CD pipelines, Docker images, Kubernetes deployments, monitoring, and operational tooling. Debug production issues across services, workflows, agents, tools, models, and infrastructure. Collaborate with engineering, product, infrastructure, and data science teams to turn requirements into reliable systems. What we need to see: 5+ years of experience and a practical understanding of how AI agents are built, including tool use, state, context, and multi-step execution. Bachelors degree or equivalent experience. Experience with at least one open-source agent or LLM application framework, such as LangChain/LangGraph. Strong software engineering background, especially in backend development. Experience with distributed systems, workflow orchestration, and prod

About the Job Lead performance work that turns large-scale AI workloads into faster, more efficient systems. As a Staff AI Performance Engineer, you will analyze and optimize AI training and inference workloads across distributed systems. Your work will connect compute, memory, networking and software behavior. You will lead complex performance workstreams across hardware and software. You will find bottlenecks, validate improvements and turn performance evidence into practical engineering decisions. You will build benchmarks, profile demanding workloads and develop C++ and Python tools for analysis and optimization. Your recommendations will help teams improve efficiency, scalability and reliability. This role gives you broad technical scope across AI infrastructure at data center scale. It is based in Milpitas, California. The team and culture The System Engineering Performance team architects, evaluates and optimizes high-performance infrastructure for large-scale data center deployments. The team works across the computing stack to understand real system behavior. Work moves through evidence, ownership and clear technical judgment. You will lead investigations, coordinate across teams and validate impact with reliable performance data. Decisions are shaped through benchmarks, models, simulations and practical engineering tradeoffs. The team values engineers who think big, act fast, take responsibility, speak up and lead beyond their own area. What we’re looking for · Strong experience profiling and optimizing AI, machine learning or high-performance computing workloads. · Experience with distributed systems and communication libraries such as MPI, NCCL, UCX or libfabric. · Strong C++ and Python skills, including reliable tools or performance-sensitive software. · Deep understanding of compute, memory and communication behavior in large-scale systems. · Ability to lead technically complex work and coordinate improvements across teams. · Familiarity with MLPerf, a

About the Job Turn complex AI workload signals into faster, more efficient systems at data center scale. As a Senior AI Performance Engineer, you will analyze and optimize AI training and inference workloads across large-scale distributed systems. Your work will connect compute, memory, communication and software behavior. You will own complex performance investigations from problem definition through validation. You will turn profiling, benchmarking and modeling results into improvements engineers can build from. You will design benchmarks, investigate system bottlenecks and optimize distributed communication software across technologies such as MPI, NCCL, UCX and RDMA. Your work will help Graphcore deliver efficient, reliable AI systems for large-scale deployment. This role gives you rare scope across hardware, software, networking and system architecture. It is based in Austin, Texas. The team and culture The System Engineering Performance team architects, evaluates and optimizes high-performance infrastructure for large-scale data center deployments. The team works across the computing stack to understand real system behavior. Work moves through evidence, ownership and clear technical judgment. You will define investigations, coordinate across teams and validate impact with reliable performance data. Decisions are shaped through benchmarks, models, simulations and practical engineering tradeoffs. The team values engineers who think big, act fast, take responsibility, speak up and lead beyond their own area. What we’re looking for · Strong experience profiling and optimizing AI, machine learning or high-performance computing workloads. · Experience with distributed systems and communication libraries such as MPI, NCCL, UCX or libfabric. · Strong C++ and Python skills, including reliable tools or performance-sensitive software. · Deep understanding of compute, memory and communication behavior in large-scale systems. · Ability to own complex technical work and coo

About DevRev At DevRev, we're building the future of work with Computer – your AI teammate. Unlike traditional tools, Computer unifies all your data sources, tools, and workflows into a single AI-ready platform, giving employees real-time insights, proactive suggestions, and powerful agentic actions. It extends your existing software with AI-native apps and agents that work alongside your teams and customers – updating workflows, coordinating across teams, and eliminating repetitive work. We call this Team Intelligence: human-AI collaboration that breaks down silos, brings people back together, and frees you to solve bigger problems. Backed by Khosla Ventures and Mayfield with $150M+ raised, DevRev is trusted by global companies across industries. About the role: We are looking for a Senior Data Engineer to help build and evolve the data platform that powers critical business decisions and customer-facing experiences. You will own significant parts of our data architecture that is main powerhouse of DevRev Computer’s memory for accurate and efficient Answers. As a part of data team, you will design and operate scalable data systems, and work closely with Software Engineering, AI Agent teams, Data Science, and Product teams to turn complex data requirements into reliable, high-quality data products. This role is ideal for an experienced engineer who enjoys solving challenging problems involving large-scale data, distributed systems, database architecture, and performance optimization . You will have significant technical ownership and the opportunity to influence the direction of our agentic data platform while helping raise the engineering bar across the team. What you'll do: Own data architecture for large-scale, high-impact projects, making thoughtful tradeoffs across scalability, reliability, performance, maintainability, and operational cost. Design, build, and operate scalable data pipelines and data systems that reliably ingest, transform, store, and se

About the Role: Site Reliability Engineering (SRE) at Tubi is not a traditional operations team. We are a software engineering organization that applies a developer's mindset and toolkit to the challenges of building and running large-scale, distributed systems. Our mission is to engineer resilience from the ground up, enabling our product teams to innovate rapidly while ensuring our users have a stellar experience. We own the availability, latency, performance, and capacity of our platform, and we achieve our goals through a culture of data-driven decision-making, blameless learning, and relentless automation. As a Senior Site Reliability Engineer, you are a hands-on engineer who blends deep software development expertise with a passion for operational excellence. You will be responsible for designing, building, and running the resilient, scalable, and increasingly self-healing systems that power our products. You will apply sound engineering principles to solve our most complex reliability challenges, with a mandate to automate everything, eliminate toil, and write robust, maintainable code. You will be a force multiplier, mentoring other engineers and elevating the site reliability bar for the entire organization. This is a hybrid role based out of our Toronto office. You must be willing to travel to our Toronto office two days/week. What You'll Do: System Architecture & Design: Design, build, and maintain scalable, highly available, and fault-tolerant distributed systems. Partner with development teams as a reliability consultant, reviewing designs and influencing architectural decisions to ensure new services are built with reliability, observability, and performance as core principles, not afterthoughts. Automation & Software Development: Write robust, performant, and maintainable code to automate operational tasks, and CI/CD pipelines. Build the internal tools, libraries, and frameworks that enable engineering teams to self-service their

Senior Cloud Security Engineer At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the Role Anyscale's security needs are growing as we operate more production and cloud infrastructure for larger and more demanding customers. We're looking for a Senior Cloud Security Engineer to own the security of that infrastructure. This is a hands-on, high-ownership role: you will own how our production and cloud environments are hardened, isolated, and monitored. You will set and drive the direction for infrastructure and production security, reporting to the Head of Security and partnering closely with the wider engineering organization. This role is based in the San Francisco, Bay Area. In your first year, success looks like hardened and well-segmented production environments, strong runtime security coverage across our container footprint, and a clear, defensible story for how we secure the infrastructure our customers rely on. What You'll Do Own the security posture of Anyscale's production and cloud infrastructure across AWS and Azure, including hardening, network segmentation, and tenant isolation. Own runtime security coverage across our Kubernetes environments, from deployment through detection of anomalous activity. Partner with engineering on secure infrastructure architectur

Join the MongoDB Server Query Optimization team, and help us build a world-class distributed open-source query optimizer. Our team plays a crucial role in the experience and performance of data processing. We are responsible for the MongoDB Query Language and the lifecycle of each query, through parsing, optimization and plan selection. We have a presence across the US and Europe including New York, Dublin, Seattle, Palo Alto, and Chicago. We support office-based and remote work and align projects with convenient work hours for each time zone. We have tons of interesting problems to solve with a direct impact on users for transactional, time-series, and analytical workloads. The team is endeavoring to systematically rewrite every major component of our optimization and execution systems. We need your help to design and build the heart of a distributed, flexible schema, document database. ​​This role can be based out of our US offices or remotely in the North America region. Candidate Profile 10+ years of experience in data management systems, distributed systems, or large-scale backend engineering Experience with building production-level code with a large user base, robust design structure and rigorous code quality Degree in Computer Science or similar field, or equivalent practical experience, with strong competencies in data structures, algorithms, and software design/architecture Experience with large code bases written in C++ or another systems programming language. You'll need to trace down defects, estimate work complexity, and design evolution and integration strategies as we rewrite different components of the system A strong foundation in core database internals is essential. While direct experience in query optimization is a massive bonus, it is not a prerequisite. We are also excited to meet candidates with strong backgrounds in compilers, language transpilers, or distributed storage systems Position Expectations Innovate in the area of flexible schema d

The Team Platform Engineering sits within SRE and builds the core infrastructure powering MongoDB’s broader engineering organization. Our teams own everything from our multi-cloud Kubernetes foundation to automated deployment pipelines and global observability platforms. Within Platform Engineering, the Fabric team manages the global network substrate that enables secure communication between internal microservices and incoming public internet traffic. We own network architecture, service mesh topologies, and edge load balancing, ensuring customer data remains safe in transit. Ultimately, Fabric plays a pivotal role in engineering the reliable, globally connected, multi-cloud network that underpins all MongoDB products. This role is based remotely in the United States. Role Overview We are seeking a talented Senior Site Reliability Engineer (SRE) with a strong networking background to join the Fabric team. This role is pivotal in building and maintaining the robust infrastructure necessary for secure and efficient communication between our services. As a Senior SRE on the Fabric team, you will leverage your expertise in networking, distributed systems, and automation to ensure our systems are resilient, scalable, and reliable. The ideal candidate should Be a US Citizen, as the position supports our FedRAMP authorized environment Have 5+ years of experience working on software and operating distributed systems, with deep expertise in networking fundamentals and a good understanding of how the internet works, e.g. TCP/IP (including IPv6), DNS, TLS/mTLS, BGP, tunnels, overlays, and SDN principles Be intimately familiar with modern cloud-based infrastructure and the network design primitives of at least one of AWS, Azure, or GCP, e.g. VPCs, subnetting, routing, VPNs, peering, private link / private service connect, and CDNs Possess a customer-focused mindset, driving improvements that benefit end-users Value efficiency in processes and operations, and display a strong p