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Distributed Systems Engineer Jobs

1,301 active opportunities · Updated for October 2026

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Explore current distributed systems engineer jobs. Use filters to narrow by work mode, employment type, experience and date posted.

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Mongodb
📍 United States• Full-time• From $109K/yr
1mo ago

The Agent Research and Tooling team, part of MongoDB's AI Builder Experience organization, owns the platform layer around agents: how teams author, distribute, evaluate, monitor, and improve agent skills and agent behavior. We are hiring a software engineer to build and maintain the tooling, evaluation systems, and quality gates behind MongoDB's agent skills. This is a software engineering role at the intersection of developer tooling, applied AI, and software quality. You will take loosely defined agent and tooling problems, break them into workable plans, and ship durable internal systems: command-line tools, reusable libraries, evaluation harnesses, and CI workflows. This role is open to remote work in the US or can be based out of any of our US offices. What you'll do Build and maintain agent skills and the infrastructure to validate, evaluate, publish, and maintain them Design evaluation datasets and workflows that compare agent behavior against a baseline and produce actionable quality signals Build agent metrics and observability: skill selection and routing, success and failure outcomes, tool calls, latency, and token usage Design safety and quality gates for agent-authored content: rule packs, static analysis, confidence thresholds, structured verdicts, and bounded suppression Create CLIs, libraries, and MCP integrations that other repositories adopt and that run in local development and CI Integrate tooling into GitHub Actions and other CI workflows, including secrets, annotations, exit codes, and artifacts Build code-generation quality checks, such as anti-pattern catalogs and linting for AI-generated MongoDB code Investigate real failures such as nondeterministic results, false positives, and unsafe generated guidance, and turn them into reusable improvements Collaborate with engineers, security partners, and product teams; communicate trade-offs, risks, and ownership across teams Examples of the problems you'll solve How can tests verify an agent tool's

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Mongodb
📍 Alberta• Full-time• From C$108K/yr
1mo ago

The Agent Research and Tooling team, part of MongoDB's AI Builder Experience organization, owns the platform layer around agents: how teams author, distribute, evaluate, monitor, and improve agent skills and agent behavior. We are hiring a software engineer to build and maintain the tooling, evaluation systems, and quality gates behind MongoDB's agent skills. This is a software engineering role at the intersection of developer tooling, applied AI, and software quality. You will take loosely defined agent and tooling problems, break them into workable plans, and ship durable internal systems: command-line tools, reusable libraries, evaluation harnesses, and CI workflows. This role is open to remote work in Canada or can be based out of any of our Canada offices. What you'll do Build and maintain agent skills and the infrastructure to validate, evaluate, publish, and maintain them Design evaluation datasets and workflows that compare agent behavior against a baseline and produce actionable quality signals Build agent metrics and observability: skill selection and routing, success and failure outcomes, tool calls, latency, and token usage Design safety and quality gates for agent-authored content: rule packs, static analysis, confidence thresholds, structured verdicts, and bounded suppression Create CLIs, libraries, and MCP integrations that other repositories adopt and that run in local development and CI Integrate tooling into GitHub Actions and other CI workflows, including secrets, annotations, exit codes, and artifacts Build code-generation quality checks, such as anti-pattern catalogs and linting for AI-generated MongoDB code Investigate real failures such as nondeterministic results, false positives, and unsafe generated guidance, and turn them into reusable improvements Collaborate with engineers, security partners, and product teams; communicate trade-offs, risks, and ownership across teams Examples of the problems you'll solve How can tests verify an agent to

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OpenAI
📍 San Francisco• Full-time
1mo ago

About the Team OpenAI’s API Multicloud team is responsible for extending OpenAI’s API platform into strategic cloud environments, starting with AWS . The team’s mission is to distribute OpenAI’s API broadly and safely by enabling key API technologies in cloud-native environments, in close partnership with Amazon and internal teams across Codex, Research, Safety Systems, and Applied. The team is focused on bringing core developer and enterprise capabilities into cloud-native environments, including cloud-hosted Codex, model customization / post-training as a service, and new stateful runtime environments for agentic workloads. This work sits at the intersection of production ML systems, developer platforms, model behavior, and large-scale infrastructure. About the Role We’re looking for a backend engineer who can quickly understand OpenAI’s models, products, and systems, then adapt first-party deployments for other cloud platforms. You’ll build backend services, APIs, SDK integrations, authentication flows, and cloud service infrastructure that let developers use OpenAI capabilities in the cloud environments where they already build. This role involves working across teams, sometimes embedded with partner product groups, to ship products quickly and across multiple platforms at the same time. It’s a strong fit for engineers who have built developer tools, especially AI-powered tools, communicate clearly across technical boundaries, and can shape architectures that support different deployment models; experience building cloud services is a strong plus. In this role, you will: Build backend and infrastructure systems that extend OpenAI’s API platform into cloud-native environments, like AWS. Design and ship cloud-contained products that allow customers to use OpenAI capabilities while keeping workloads and data within cloud environments. Help stand up cloud-hosted Codex experiences powered by the OpenAI Responses API. Build the infrastructure and runtime abstractions

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OpenAI
📍 San Francisco• Full-time
1mo ago

About the team The Applied team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the role: We're seeking a Data Engineer to take the lead in building our data pipelines and core tables for OpenAI. These pipelines are crucial for powering analyses, safety systems that guide business decisions, product growth, and prevent bad actors. If you're passionate about working with data and are eager to create solutions with significant impact, we'd love to hear from you. This role also provides the opportunity to collaborate closely with the researchers behind ChatGPT and help them train new models to deliver to users. As we continue our rapid growth, we value data-driven insights, and your contributions will play a pivotal role in our trajectory. Join us in shaping the future of OpenAI! In this role, you will: Design, build and manage our data pipelines, ensuring all user event data is seamlessly integrated into our data warehouse. Develop canonical datasets to track key product metrics including user growth, engagement, and revenue. Work collaboratively with various teams, including, Infrastructure, Data Science, Product, Marketing, Finance, and Research to understand their data needs and provide solutions. Implement robust and fault-tolerant systems for data ingestion and processing. Participate in data architecture and engineering decisions, bringing your strong experience and knowledge to bear. Ensure the security, integrity, and compliance of data according to industry and company standards. You might thrive in this role if you: Have 3+ years of experience as a data engineer and 8+ years of any software engineering experience(including data engineering). Proficiency in at least one programming language commonl

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1mo ago

Join the engineering teams that bring OpenAI’s ideas safely to the world!! The Applied Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role As OpenAI continues to grow, we are looking for experienced, problem-solving engineers to ensure our systems scale. Our success depends on our ability to quickly iterate on products while also ensuring that they are performant and reliable. You will work in a deeply iterative, collaborative, fast-paced environment to bring our technology to millions of users around the world, and ensure it’s delivered with safety and reliability in mind. Successful candidates will play a crucial role in ensuring the reliability, scalability, and performance of our systems as we continue to expand. As a reliability expert, you will be at the forefront of maintaining and enhancing the stability, scalability, and performance of our rapidly evolving infrastructure. You will work closely with cross-functional teams, including software engineers, product managers, and data scientists, to build and maintain resilient systems that can handle our growing user base and workload. In this role, you will: Design and implement solutions to ensure the scalability of our infrastructure to meet rapidly increasing demands. Build and maintain the load, chaos and synthetic testing software leveraged by development teams to make the systems they design and operate more reliable. Build and maintain automation tools to streamline repetitive tasks and improve system reliability. Build and maintain the platform for CPU/storage, GPU, and network lifecycle management to drive efficiency, accountability and support dynamic optimization of our resources. Implement fault-tolerant and resilient

awskubernetesrest
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Remote Web Developer (Equity Partner 10%) Role Type: Founding Web Developer (Equity-Based) Location: Remote Experience: Freshers Welcome (Strong builders preferred) Compensation: 10% Equity (Vesting-Based) Cash Compensation: None initially About the Startup We are building two high-impact digital platforms: 1️ Solar Fintech Platform A fractional ownership platform where: • Users buy micro-shares (e.g., 100 units) of solar panels. • Once fully funded, solar panels are deployed to corporates. • Energy generation produces returns distributed proportionally to shareholders. Core Components: • Investor dashboard • Payment integration • Solar performance analytics • Admin & corporate PPA tracking 2️ Carpooling Platform (Similar to Mitfahrgelegenheit) A ride-sharing website connecting drivers and passengers traveling between cities. Core Components: • Driver ride listing system • Seat booking & payment • Route matching • Ratings & verification • Real-time notifications Role Overview As a Founding Web Developer, you will architect, build, and deploy both platforms from scratch. You are not just a coder you are a technical co-builder. Key Responsibilities Product Development • Develop full-stack web applications (frontend + backend) • Build scalable database architecture • Implement secure payment gateway integrations • Develop admin dashboards • Deploy MVP and iterate rapidly Solar Fintech Specific • Micro-share allocation logic • Wallet & transaction history system • Solar data API integration • ROI calculation engine • Investor performance dashboard Carpooling Platform Specific • Ride-matching algorithm • Location-based search • Booking & seat allocation system • Driver/passenger profile system Infrastructure • Cloud deployment (AWS / GCP / Azure) • CI/CD pipelines • Basic cybersecurity implementation • API architecture Skills Required • React / Next.js / Vue (Frontend) • Node.js / Django / Laravel (Backend) • SQL / NoSQL databases • Payment gateway integration exper

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Coinbase
📍 - USA• Full-time• Remote• From $207.5K/yr
1mo ago

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . Team/ Role Paragraph: Coinbase is building the future of institutional trading as part of the Everything Exchange, powering the systems that let the world's largest financial institutions trade across markets with speed, depth, and trust. As a Market Data Engineer on the Markets team, you'll architect, build and own the systems that generate, capture, normalize, and distribute real-time market data across Coinbase at low latency - the ticker plant and distribution backbone of a unified trading platform - while leading a lean, high-impact team. It's a rare chance to architect market data infrastructure from the ground up, with the ownership of a startup and the reach of Coinbase. What you’ll do: Build and operate market data components: feed handlers, normalization, distribution, and venue connectivity. Design low-latency, high-throughput systems for real-time market data used by trading systems. Contribute to reliability and performance, participating in observability, on-call, and incident response. Write high-quality, well-tested code and help raise the quality bar on a lean team. Partner with engineers, product, and cross-functional stakeholders to deliver market data capabilities. Required skills and experience: 5+ years of backend engineering, with experience building and maintaining production low-latency systems. Hands-on experience with market data syst

REMOTEjavaawsai
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C
1mo ago

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Large Language Models (LLMs) continue to push the boundaries of what AI systems can do — but inference is still the bottleneck. The Model Efficiency team is responsible for pushing the limits of LLM inference efficiency across our foundation models. We explore and ship breakthroughs across the model execution stack, including: model architecture and MoE routing optimization decoding and inference-time algorithm improvements software/hardware co-design for GPU acceleration performance optimization without compromising model quality Please Note: We have offices in Toronto, Montreal, San Francisco, New York, Paris, Seoul and London. We embrace a remote-friendly environment, and as part of this approach, we strategically distribute teams based on interests, expertise, and time zones to promote collaboration and flexibility. You'll find the Model Efficiency team concentrated in the EST and PST time zones, these are our preferred locations. As a Staff Research Engineer, you will develop, prototype, and deploy techniques that materially improve how fast and efficiently our models run in production. You may be a good fit

gitrestmachine learning
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Mongodb
📍 Gurugram• Full-time
1mo ago

The IT SaaS Engineering Team plays a critical role in optimizing MongoDB sales processes, streamlining customer interactions, and maximizing the efficiency of our sales efforts. By leveraging Salesforce, the team ensures that business users have the tools, automation, security, and governance needed to effectively manage customer relationships, support operational processes, and drive business growth. With deep expertise in Salesforce development, platform governance, automation, and system operations, the team continuously enhances the CRM platform to meet evolving business needs. The team partners closely with stakeholders across Sales Operations, Revenue Operations, Security, Compliance, and Engineering to deliver scalable, secure, and reliable Salesforce solutions. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Role Overview We are looking for a highly capable Senior Salesforce Engineer to design, build, and maintain scalable CRM solutions that support MongoDB’s Sales organization. This role combines strong hands-on Salesforce development, solution design, cross-functional collaboration, and a modern engineering mindset to deliver reliable, maintainable, and high-quality solutions across the core Salesforce platform. What you’ll do Design, build, and maintain scalable Salesforce solutions across the core CRM platform, including custom development, automation, and integrations Partner with business stakeholders, program managers, and technical teams to understand requirements and translate them into secure, maintainable, and scalable technical solutions Own delivery across the full solution lifecycle, including design, development, testing, deployment, documentation, and production support Collaborate closely with globally distributed engineering teams to deliver reliable, secure, and well-governed solutions in an Agile environment Drive strong engineering practices across code quality, documentation, release managem

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Mongodb
📍 New York City• Full-time• From $118K/yr
1mo ago

The IT SaaS Engineering Team plays a critical role in optimizing MongoDB sales processes, streamlining customer interactions, and maximizing the efficiency of our sales efforts. By leveraging Salesforce, the team ensures that business users have the tools, automation, security, and governance needed to effectively manage customer relationships, support operational processes, and drive business growth. With deep expertise in Salesforce development, platform governance, automation, and system operations, the team continuously enhances the CRM platform to meet evolving business needs. The team partners closely with stakeholders across Sales Operations, Revenue Operations, Security, Compliance, and Engineering to deliver scalable, secure, and reliable Salesforce solutions. We are looking to speak to candidates who are based in New York for our hybrid working model. Role Overview We are looking for a highly capable Senior Salesforce Engineer to design, build, and maintain scalable CRM solutions that support MongoDB’s Sales organization. This role combines strong hands-on Salesforce development, solution design, cross-functional collaboration, and a modern engineering mindset to deliver reliable, maintainable, and high-quality solutions across the core Salesforce platform. We are looking to speak to candidates who are based in New York City, NY for our hybrid working model. What you’ll do Design, build, and maintain scalable Salesforce solutions across the core CRM platform, including custom development, automation, and integrations Partner with business stakeholders, program managers, and technical teams to understand requirements and translate them into secure, maintainable, and scalable technical solutions Own delivery across the full solution lifecycle, including design, development, testing, deployment, documentation, and production support Collaborate closely with globally distributed engineering teams to deliver reliable, secure, and well-governed solutions in an A

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Lyft
📍 San Francisco• Full-time
1mo ago

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. We are hiring a Machine Learning Engineer to join our ETA team. Our team builds and maintains Lyft's system responsible for estimating/predicting ETAs for every ride request on our platform. ETAs play a critical role in matching decisions, pricing estimates and overall user experience. Low latency, high reliability and high accuracy are paramount for our success. If you are a critical thinker with experience in machine learning workflows and writing reliable code, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. Our technology stack runs on AWS, Kubernetes, Go, Spark, Python and Apache Airflow. In this role, you will work with incredibly passionate and talented colleagues from software engineering, machine learning and data science on building rideshare experiences that delight millions of riders and drivers. Responsibilities: Perform data analysis and build proof-of-concept to explore and compare ML and non-ML solutions Be able to make effective tradeoffs between model accuracy, its productization complexity and runtime performance Develop statistical, machine learning, or optimization models Write production quality code that can scale well to serve millions of requests per day Participate in code reviews, design reviews, production on-call support and incident triaging process. Write well-crafted, well-tested, readable, maintainable code Experience: B.S., M.S., or Ph.D. in Computer Science or other quantitative fields or related work experience 3+ years of Machine Learning experience Nice-to-have: Experience with big data processing / distributed data pipelines and tools such as Apache Airflow and Spark Ability to work in distributed teams spread across time zones. (North America and

pythonawskubernetes
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Lyft
📍 Toronto• Full-time• From C$136K/yr
1mo ago

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. Lyft is looking for experienced software engineers from a variety of disciplines. We are growing our team with people who want to build, improve and incorporate technologies that make the lives of our community more enriched. As an engineer at Lyft, you'll collaborate with teams like product, data science, analytics, and operations on code that empower us to iterate quickly, while focusing on delighting our passengers and drivers. As a Senior Software Engineer on the Marketplace team, you will lead work streams to improve business operations in Lyft’s Marketplace. You'll design AI driven data analytics platforms, data pipelines and metric governance systems that our business leaders use on a daily basis to make key strategic decisions. You will partner with business leaders and data scientists across our organizations to enable running the business more efficiently. Responsibilities: Help define the roadmap and architecture based on technology and business needs Drive AI innovation for business analytics and operations 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 knowledge Lead projects from idea to positive execution Incorporate considerations for business context and failure modes in your work Proactively participate in resolving ongoing incidents Unblock, support, effectively communicate, and obtain buy-in across teams to achieve results Share your knowledge by giving brown bags, tech talks, and evangelizing appropriate tech and engineering best practices Experience: 5+ years of software engineering industry experience with a high level programming language (bonus points for experience with Python or Go) AI Experience in Agen

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1mo ago

Who we are About Stripe Stripe 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. About the team The Issuing team owns the Stripe card issuing product end to end from the APIs and backend services that power spend cards, debit cards, and charge cards, to the dashboard and embedded components that businesses use to manage their card programs. We build the infrastructure and interfaces that let platforms and businesses instantly create, distribute, and control payment cards at scale, and we're responsible for the full cardholder lifecycle across commercial and consumer issuing. We're at an inflection point. Issuing is expanding into new geographies, new card categories (stablecoin, healthcare, consumer credit), and deeper partnerships with major platforms. This is a high-impact, high-visibility role at the intersection of financial infrastructure, developer-facing APIs, and end-user product experience, and it requires someone who can lead technically across a complex, fast-moving domain. What you'll do Define and drive the technical strategy for Issuing, including multi-year architecture decisions across backend services, APIs, and user-facing surfaces. Own end-to-end technical solutions for critical systems, authorization flows, spending controls, cardholder management, and card program configuration, ensuring they are reliable, scalable, and operationally sound. Identify and lead infrastructure investments that unlock new issuing models, including geographic expansion, new card program types, and platform-level extensibility

About the Team We bring OpenAI's technology to the world through products like ChatGPT and the OpenAI API. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role We are looking for an experienced Research Engineer to work on retrieval & search problems across our API and ChatGPT. As the AI landscape has evolved over the last few years, retrieval & search have emerged as key use cases for our models, and we are investing in ensuring that we can offer these search-based product experiences for our users. You will be at the center of our retrieval & search efforts as a company, and the progress you drive here will reach millions of end users. In this role, you will: Work on retrieval & search algorithms and methodologies in close collaboration with our research team, including problems in such domains as document search, enterprise search, knowledge retrieval, and web-scale search. Deploy these search methodologies into production in both the API and ChatGPT to be used by millions of end users. Explore novel research topics in retrieval & search that may inform our product strategy in the medium and long term. Partner with researchers, engineers, product managers, and designers to bring new features and research capabilities to the world You might thrive in this role if you: Have extensive prior experience building and maintaining production machine learning systems. Have prior experience working with vector databases, search indices, or other data stores for search and retrieval use cases Have prior experience building and iterating on internet-scale search systems Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done Have the ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or de

awsrestmachine learning
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O
1mo ago

About the Team The Applications Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. You’ll join the team responsible for running the core infrastructure that supports products like ChatGPT and the API. The systems we support include our kubernetes clusters, infrastructure deployment, our networking stack, cloud abstractions, and more. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role The cloud infrastructure team builds and maintains infrastructure abstractions allowing OpenAI to ship products quickly and scalably. In this role, you will: Design and build the development and production platforms that power our products, enabling reliability and security at scale Ensure our infrastructure can scale to the next order of magnitude Help create a diverse, equitable, and inclusive culture that makes all feel welcome while enabling radical candor and the challenging of group think Like all other teams, we are responsible for the reliability of the systems we build. This includes an on-call rotation to respond to critical incidents as needed. You might thrive in this role if you: Have 5+ years building core infrastructure Have experience operating orchestration systems such as Kubernetes at scale Have experience building abstractions over cloud platforms Take pride in building and operating scalable, reliable, secure systems Are comfortable with ambiguity and rapid change 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

awskubernetesrest
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