Software Engineer Distributed Systems Jobs

Who we are At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences. Our dedication to remote-first work , and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. . Hiring and how we work We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings. . See yourself at Twilio Join the team as our next Software Engineer (L2) Who we are & why we’re hiring Twilio powers real-time business communications and data solutions that help companies and developers worldwide build better applications and customer experiences. Although we're headquartered in San Francisco, we're on a journey to becoming a globally antiracist company that supports diversity, equity & inclusion wherever we do business. We employ thousands of Twilions worldwide, and we're looking for more builders, creators, and visionaries to help fuel our growth momentum. About the job This position is needed to fulfill the critical role of a Software Engineer within Twilio Sendgrid, to be both hands-on in creating, deploying and managing highly available, very large scale distributed systems. Our systems processed 12 billion emails on Black Friday 2026 and we continue to scale! You will be a key contributor in one or more of these areas -&nbs

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Marketplace teams are at the heart of our products and decision-making, owning everything from rider pricing to driver earnings, incentives, and efficient matching. We’re looking for passionate, driven engineers to build systems that empower our riders and drivers to have the best transportation experience possible through prediction, adaptivity, and personalization. We’re looking for someone who is excited about working in a fast-paced, innovative, and impactful environment to create reliable solutions to distributed computing, ML, and data problems. The Pricing team is a centerpiece of Lyft’s Marketplace org, determining prices for all rideshare products and supporting new initiatives. Rider Engagement develops rider-facing engagement levers and optimizes user pricing experience to drive both short term and long term business outcomes. We work with Product & Science to solve and implement complex pricing requirements, balancing the needs of riders, drivers, and the business goals. As an owner of one of the most critical flows in the company, you will work on a wide array of challenges such as latency-sensitive concurrency problems, large scale distributed systems, and experimentation. If you’re interested in playing a large part in demand / supply management and improving the Lyft customer experience, this could be a great fit for you. Responsibilities: Drive high-impact projects and innovate new solutions to provide the best user experience. Work closely with cross-functional teams and partner teams to develop solutions based on technology and business needs, and advance team’s goals and priorities Independently lead features from idea to positive execution and launch Unblock, support and communicate with internal partners to achieve results Write well-crafted, well-tested, readable, maintaina

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Our Infrastructure team is passionate about building software to solve problems at massive scale. We do this often, and when we believe our solution is worth sharing with the community, such as Envoy Proxy , we open source our ideas for the benefit of others. As an Observability team member, you are responsible for the operation and maintenance of our logging and metrics infrastructure. You ensure all teams at Lyft are aware of the operational health of their products by monitoring system availability and take a holistic view of our platform performance. You build software and platforms to automate infrastructure platform operations and management. By measuring and monitoring our operations you find opportunities to improve our systems in order to push our platform forward. You provide our partners with the support they need to help them build robust large scale distributed systems. We count on the reliability of our infrastructure to empower Lyft teams to provide our customers rich experiences that are highly available with rock solid performance to ensure our transportation platform continues to connect people and places. As we grow our team, we are seeking experienced Infrastructure Engineer to ensure that as our Infrastructure continues to scale, our platform continues to provide an essential and dependable service that transports millions of people every day. Specifically we are searching for someone who brings fresh perspectives, enjoys collaborating with cross-functional teams in order to continually improve our products and services for our customers. Responsibilities: Maintain, improve, and develop tooling and systems that enhance the reliability, scalability, and efficiency of our platform. Assist engineering teams in defining service-level objectives (SLOs) and provide the necessary toolin

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Core Services powers the passenger and driver state machines from request and accept through drop-off and payment completion. The team enables new ride variations like autonomous vehicles, taxis, scheduled, business concierge, health and more. The “Core Services” are a suite of distributed Python and Golang systems central to Lyft’s backend. As a software engineer on the team, you will work on integrating new rider and driver products and features onto the state machine and enhancing the performance and reliability of ride state transitions. If you are excited about solving back-end distributed systems problems and owning a mission-critical part of Lyft’s operations, this team is for you. As a Software Engineer at Lyft, you will collaborate with other engineers and cross-functional teams, such as product, data science, and analytics, to lead and execute large projects—from concept to efficient execution. We are looking for motivated engineers who are passionate about solving challenging technical problems and excited to work in a fast-paced, innovative, and cross-functional environment. In this role, you will tackle some of the most interesting and impactful problems in ridesharing. Key traits for success include being passionate about Lyft’s business and product, a quick learner, a collaborative mindset, and an eagerness to drive initiatives both within and across teams. You'll be joining a small, close-knit team with engaged and collaborative co-workers. Responsibilities: Design, develop, deploy, monitor, operate and maintain existing or new elements of the Fulfillment tech stack Write well-crafted, well-tested, readable, maintainable code Have a good grasp and ability to explain the various tradeoffs made in decisions Participate in code reviews to ensure code quality and distribute knowledg

Role Description As a Software Engineer on the Metadata team, you’ll build and operate the large-scale distributed databases that every Dropbox service depends on. Metadata systems are mission-critical, in the live path for all user operations and must meet stringent requirements for latency, durability, and transactional consistency. You’ll design and evolve the core infrastructure that manages Dropbox’s databases at scale, enabling fast, reliable access to data for millions of users and hundreds of internal services. This work spans distributed systems, replication, caching, and transactional database systems. You’ll collaborate closely with engineers across Infrastructure and Product teams to ensure the metadata layer meets business needs and continues to scale with Dropbox’s growth. This is an opportunity to leverage your expertise in distributed systems and grow into broader technical leadership. Our Engineering Career Framework is viewable by anyone outside the company and describes what’s expected for our engineers at each of our career levels. Check out our blog post on this topic and more here . Responsibilities Design and maintain distributed database systems providing low-latency, strongly consistent data access Implement and optimize replication, consensus, and caching mechanisms to meet availability and performance goals Operate production systems, including participating in the on-call rotation, ensuring high availability and data durability Collaborate with infrastructure and product teams to assess current and future use cases and requirements, supporting the development of a mid- to long-term roadmap that reflects these needs Contribute to system design reviews, postmortems, and reliability improvements Write high-quality, efficient code in Go and Rust for performance-critical systems On-call work may be necessary occasionally to help address bugs, outages, or other operational issues, with the goal of maintaining a stable and high-quality experienc

Who we are About Stripe Stripe, LLC. is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. What you’ll do Responsibilities Design, develop, maintain, and support application programming interfaces (APIs), backend services, and distributed systems using Ruby, Java, Go and Scala. Build, test, deploy, and maintain software infrastructure to support large-scale production systems. Design and develop software systems using analytical techniques and mathematical models to evaluate system performance, predict outcomes, and assess design tradeoffs. Develop and execute software testing, validation, debugging, and documentation procedures to ensure system reliability and performance. Diagnose and resolve production issues across multiple services and layers of the technology stack. Analyze user needs and software requirements to determine technical feasibility, design approaches, and implementation timelines within cost and resource constraints. Collaborate with cross-functional engineering teams to design and implement new features for large-scale systems. Design and build systems to securely store, manage, and modify production data and services. Improve engineering standards, development tools, and software development processes to enhance system quality and efficiency. Who you are Minimum requirements Must have a Bachelor's degree or foreign equivalent in Computer Science, Software Engineering, or a related field, plus 2 years of software development experience. Must also have 2 years of experi

About the Team API Multimodal builds the developer-facing products and infrastructure that bring OpenAI’s image, audio, and real-time model capabilities into the world. We are responsible for high-scale APIs for image generation, speech transcription, speech generation, and low-latency voice interactions. We partner closely with Research and Inference to bring frontier model capabilities to developers and use customer feedback to improve our models. About the Role As a software engineer on API Multimodal, you will build and operate the products and distributed systems behind OpenAI’s image, audio, and real-time APIs. You will work across model integration, API design, and production infrastructure to turn new research capabilities into reliable developer experiences. This hands-on role combines backend and systems depth with product judgment: you will own projects end to end, partner with Research, Inference, and Safety, and help make multimodal AI useful at scale. Model training experience is not required. In this role, you will: Design, build, and ship developer-facing APIs and backend services that serve frontier models. Architect low-latency streaming, request, session, and model integration systems that make complex multimodal interactions reliable and intuitive at scale. Work directly with Research to bring new model capabilities into production, shape the systems around them, and incorporate feedback from real-world developers and customers. Own the availability, latency, scalability, and cost efficiency of the services you build. Own projects from technical design and implementation through launch and ongoing iteration, while raising the team’s engineering standards. Your background might look something like: 7+ years of professional experience, excluding internships, in backend, infrastructure, platform, or product engineering roles. A track record of designing, building, and operating production backend services, developer-facing APIs, or distributed syste

About the Team The Monetization team is a cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products, including next-generation ads experiences that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation. Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers and businesses. This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring research breakthroughs into real-world systems at global scale. About the Role We’re looking for an experienced Software Engineer to build measurement systems that connect ad interactions to meaningful advertiser outcomes while protecting user privacy. In this foundational role, you’ll design infrastructure for conversion signals, attribution, reporting, and feedback loops across OpenAI’s ads products. This role is ideal for engineers who have built large-scale ads measurement, data, experimentation, marketplace, or distributed systems and want to apply that experience in a highly ambiguous 0→1 environment. You’ll work across event collection and normalization, deduplication and matching, attribution and modeled measurement, privacy-safe aggregation, reporting, and high-quality labels for ads optimization. We are hiring engineers who can independently own complex systems, make sound technical tradeoffs, and help define what should be built. You’ll work closely with Ads Delivery, Ads ML, Product, Research, Privacy, Data Sc

About the Team The Storage Infrastructure team builds and operates the storage foundation behind OpenAI’s most demanding workloads. We work directly with research to design storage systems for rapidly evolving experiments, while also powering production at scale. We own the platform end to end: backend systems, user-facing services and APIs, and the control planes that manage how data is placed, moved, and retained over time. Our stack spans cloud and in-house object stores across very different workload profiles, from GPU-attached systems to dedicated storage hardware. We also build the federation layer that unifies these backends behind a simple interface and routes each workload to the right storage solution. About the Role You will help build the storage platform that powers OpenAI’s research and production systems. This is a hands-on infrastructure role for engineers who want to work on deeply technical systems at scale and own them in production. You’ll work across object storage, cross-region data movement, lifecycle management, and the federation layer that provides a unified interface across multiple backends. Much of our stack runs on Kubernetes, and we primarily build services in Rust. In this role, you will: Build and operate storage services that underpin OpenAI’s research infrastructure Develop object storage systems across cloud and in-house environments Build systems for cross-region data movement, replication, and recovery Design lifecycle management capabilities that keep data durable, available, and cost-effective Evolve the federation layer that unifies multiple backend systems behind a simple interface Improve performance, reliability, and operational excellence across the platform Collaborate closely with researchers and infrastructure teams to support rapidly evolving workloads You might thrive in this role if you: Have experience building or operating distributed systems in production Have worked on storage infrastructure, object stores, dist

About the Team The Core Services team is responsible for building and managing foundational services. It acts as the bridge between core infrastructure (e.g. compute, storage, networking) and product engineering teams, and enables product teams to move fast, build reliably, and scale efficiently. About the Role As a software engineer in the core services team, you will design and operate critical backend platforms such as caching systems, workflow orchestration, metadata stores, and file services. You’ll focus on building highly reliable, scalable, and performant systems that serve as the backbone of our products. We’re looking for people who are passionate about building infrastructure that empowers product teams, love working on distributed systems challenges, and enjoy creating well-designed APIs and abstractions that accelerate development. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design, build, and maintain shared infrastructure services such as caching layers, workflow orchestration (Temporal), metadata stores, and file storage services. Collaborate with product teams to provide scalable, reliable primitives that abstract the complexities of distributed systems. Improve performance, resilience, and scalability of core services that power customer-facing applications. You might thrive in this role if you: Have experience with distributed systems, caching infrastructure (e.g., Redis, Memcached), metadata storage (e.g., FoundationDB), or workflow orchestration (e.g., Temporal, Cadence). Have experience running containerized services in cloud environments and integrating them into automated build/test/release (CI/CD) workflows. Understand trade-offs in consistency models, replication strategies, and performance optimization in multi-region systems. Excel at communication and collaboration with cross-functional teams, and are obsesse

About the Team The Workload team is responsible for designing and running OpenAI’s LLM training and inference infrastructure that powers frontier models at massive scale. Our systems unify how researchers train and serve models, abstracting away the complexity of performance, parallelism, and execution across vast GPU/accelerator fleets. By providing this foundation, the Workload team ensures that researchers can focus on advancing model capabilities while we handle the scale, efficiency, and reliability required to bring those models to life. About the Role We are looking for an engineer to design and implement the dataset infrastructure that powers OpenAI’s next-generation training stack. You will be responsible for building standardized dataset interfaces, scaling pipelines across thousands of GPUs, and proactively testing performance bottlenecks. In this role, you will collaborate closely with the multimodal researchers, and other infra groups to ensure datasets are unified, efficient, and easy to consume. In this role, you will: Design and maintain standardized dataset APIs, including for multimodal (MM) data that cannot fit in memory. Build proactive testing and scale validation pipelines for dataset loading at GPU scale. Collaborate with teammates to integrate datasets seamlessly into training and inference pipelines, ensuring smooth adoption and a great user experience. Document and maintain dataset interfaces so they are discoverable, consistent, and easy for other teams to adopt. Establish safeguards and validation systems to ensure datasets remain reproducible and unchanged once standardized. Debug and resolve performance bottlenecks in distributed dataset loading (e.g., straggler systems slowing global training). Provide visualization and inspection tools to surface errors, bugs, or bottlenecks in datasets. You might thrive in this role if you: Have strong engineering fundamentals with experience in distributed systems, data pipelines, or infrastructure.

About the Team The Monetization team is a new cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products—including next-generation ads experiences—that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation. Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers and businesses. This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring research breakthroughs into real-world systems at global scale. About the Role We’re looking for an experienced Software Engineer to help build the core infrastructure behind OpenAI’s monetization and ads systems. In this foundational role, you’ll architect and implement distributed systems that power OpenAI’s monetization stack—focusing on reliability, performance, privacy, and large-scale operation. You’ll work across backend, systems, and platform layers to define and implement 0→1 infrastructure, partnering closely with Product, Design, and Research to shape the future of monetized AI experiences. Your work will enable both internal and external teams to build on safe, scalable, and robust monetization primitives. This role is exclusively based across our San Francisco & Seattles sites. We offer relocation assistance to new employees. In this role, you will: Design and build the foundational backend and infrastructure powering OpenAI’s monetization and ads systems Architect large-scale distributed systems that

About the Team The Codex Core Agent team builds the kernel of Codex. We own making the agent better, accelerating research, and making those improvements real in production for our users. That means working across the systems that make Codex actually function as an agent in the real world: the production performance envelope around tokens, latency, reliability, cost, and capacity; the core execution loop and interfaces that turn models into useful behavior; the shared infrastructure that enables other teams to build on Codex; and the feedback loops that turn real-world usage into better models and better agent behavior over time. About the Role We’re looking for engineers to build the infrastructure that powers Codex agents in production. This role focuses on the systems that let models safely execute code, interact with tools, complete long-running tasks, and operate reliably and efficiently at scale. You’ll design and operate the infrastructure behind sandboxed execution, orchestration, stateful workflows, app-server and SDK boundaries, and model rollouts. You’ll work at the intersection of distributed systems, developer tooling, and AI, building primitives that make Codex faster, safer, more reliable, and easier for the rest of the organization to build on. What You’ll Do Design and build execution environments for AI agents, including sandboxing, isolation, and reproducibility. Develop systems for agent orchestration across multi-step, tool-using workflows. Build infrastructure for running, testing, and debugging code generated by models. Create state and memory systems that allow agents to persist context across long-running tasks. Optimize tokens, latency, reliability, and cost across Codex’s production fleet. Support model rollouts, capacity planning, and the core tradeoffs between quality, speed, and economics to manage a fleet of frontier agents at scale. Build shared platform capabilities that unblock product teams, partner teams, and open source Codex. Yo

About the Team Our team analyzes inference stack performance across the application, model, and fleet layers to identify bottlenecks and drive faster, cheaper inference. We combine systems profiling, benchmarking, and analysis to understand where time and cost are spent, then turn that understanding into performance optimizations and models that project performance and capacity needs for future launches. About the Role In this role, you will model inference performance across application, model, and fleet layers with higher fidelity. You will build cost-to-serve estimates from microbenchmarks and create tools that help cross-functional teams reason about latency, capacity, utilization, and cost tradeoffs. In this role, you will Build and refine performance models that translate microbenchmark results into cost-to-serve estimates. Analyze inference workloads end to end across applications, models, and fleet infrastructure. Enhance tooling to identify bottlenecks across layers for latency and throughput. Partner with other teams to turn performance insights into concrete improvements and project how future changes affect inference. You might thrive in this role if you: Enjoy reasoning from first principles about distributed systems, model inference, and hardware efficiency. Are comfortable working across abstraction layers, from application behavior to kernels, accelerators, networking, and fleet scheduling. Have deep expertise with performance profiling, benchmarking, analysis, and optimization. Enjoy collaborating with engineering and research teams to improve real production systems. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve o

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