Distributed Systems Engineer Jobs

MongoDB Technical Services Engineers use their exceptional problem solving and customer service skills, along with their deep technical experience, to advise customers and to solve their complex MongoDB problems. Technical Service Engineers are experts in the entire MongoDB ecosystem - database server, drivers, cloud and infrastructure. This also includes services such as Atlas (database as a service), or Cloud Manager (which helps customers with automation, backup and monitoring of their MongoDB systems). Our engineers combine their MongoDB expertise with passion, initiative, teamwork and a great sense of humor to help our customers to be successful with MongoDB. We are looking to speak to candidates who are based in Bengaluru for our hybrid working model. Cool things you’ll do You'll be working alongside our largest customers, solving their complex challenges - resolving questions on architecture, performance, recovery, security, and everything in between. You'll be an expert resource on best practices in running MongoDB at scale, whatever that scale may be. You'll be an advocate for customers' needs - interfacing with our product management and development teams on their behalf. And you'll contribute to internal projects, including software development of support tools for performance, benchmarking, and diagnostics. What you need We consider all candidates with an eye for those who are self-taught, insatiably curious, and multi-faceted. The ideal candidates should have strong technical experience in one (or more) of the following areas Systems administration Distributed systems Network Administration Database architecture and administration Application Architecture Data architecture and design Performance tuning and benchmarking Extra bonus points if you have experience in one or more of Java, Python, Ruby, C, C++, C#, Javascript, node.js, Go, PHP, or Perl If you have an operations background, we prefer experience administering large-scale production environments

MongoDB Technical Services Engineers use their exceptional problem solving and customer service skills, along with their deep technical experience, to advise customers and to solve their complex MongoDB problems. Technical Service Engineers are experts in the entire MongoDB ecosystem - database server, drivers, cloud, and infrastructure. This also includes services such as Atlas (database as a service), or Cloud Manager (which helps customers with automation, backup and monitoring of their MongoDB systems). Our engineers combine their MongoDB expertise with passion, initiative, teamwork, and a great sense of humor to help our customers be successful with MongoDB. We are looking to speak to candidates who are based in Bengaluru for our hybrid working model. Cool things you’ll do You'll be working alongside our largest customers, solving their complex challenges - resolving questions on architecture, performance, recovery, security, and everything in between. You'll be an expert resource on best practices in running MongoDB at scale, whatever that scale may be. You'll be an advocate for customers' needs - interfacing with our product management and development teams on their behalf. And you'll contribute to internal projects, including software development of support tools for performance, benchmarking, and diagnostics. What you need We consider all candidates with an eye for those who are self taught, insatiably curious, and multi-faceted. The ideal candidates should have strong technical experience in more than one of the following areas Systems administration Distributed systems Network administration Database architecture and administration Application architecture Experience with authentication systems such as OIDC/SAML, LDAP, Kerberos, AD etc. Experience with virtualization - docker, kubernetes If you have an operations background, we prefer experience administering large-scale production environments, including hardware, operating systems (e.g. Linux, Windows),

MongoDB Technical Services Engineers use their exceptional problem solving and customer service skills, along with their deep technical experience, to advise customers and to solve their complex MongoDB problems. Technical Service Engineers are experts in the entire MongoDB ecosystem - database server, drivers, cloud and infrastructure. This also includes services such as Atlas (database as a service), or Cloud Manager (which helps customers with automation, backup and monitoring of their MongoDB systems). Our engineers combine their MongoDB expertise with passion, initiative, teamwork and a great sense of humor to help our customers to be successful with MongoDB. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Following the successful completion of the probationary period, the candidate ​may be required to work a Tuesday-to-Saturday schedule, with Sundays and Mondays designated as weekly days off​. Cool things you’ll do You'll be working alongside our largest customers, solving their complex challenges - resolving questions on architecture, performance, recovery, security, and everything in between. You'll be an expert resource on best practices in running MongoDB at scale, whatever that scale may be. You'll be an advocate for customers' needs - interfacing with our product management and development teams on their behalf. And you'll contribute to internal projects, including software development of support tools for performance, benchmarking, and diagnostics. As an ideal candidate, you will have We consider all candidates with an eye for those who are self taught, curious, and multi-faceted. Our ideal ATSE II candidate should have: 4+ years of relevant experience Strong understanding and grasp of the following areas Systems administration Troubleshooting Systems Scalable and Highly available distributed systems Network Administration Application Architecture Data architecture and design Understanding of database archit

MongoDB Technical Services Engineers use their exceptional problem solving and customer service skills, along with their deep technical experience, to advise customers and to solve their complex MongoDB problems. Technical Service Engineers are experts in the entire MongoDB ecosystem - database server, drivers, cloud and infrastructure. This also includes services such as Atlas (database as a service), or Cloud Manager (which helps customers with automation, backup and monitoring of their MongoDB systems). Our engineers combine their MongoDB expertise with passion, initiative, teamwork and a great sense of humor to help our customers to be successful with MongoDB. We are looking to speak to candidates who are based in Dublin for our hybrid working model. Cool things you’ll do You'll be working alongside our largest customers, solving their complex challenges - resolving questions on architecture, performance, recovery, security, and everything in between. You'll be an expert resource on best practices in running MongoDB at scale, whatever that scale may be. You'll be an advocate for customers' needs - interfacing with our product management and development teams on their behalf. And you'll contribute to internal projects, including software development of support tools for performance, benchmarking, and diagnostics. What you need We consider all candidates with an eye for those who are self-taught, insatiably curious, and multi-faceted. The ideal candidates should have strong technical experience in one (or more) of the following areas Systems administration Distributed systems Network Administration Database architecture and administration Application Architecture Data architecture and design Performance tuning and benchmarking Extra bonus points if you have experience in one or more of Java, Python, Ruby, C, C++, C#, Javascript, node.js, Go, PHP, or Perl If you have an operations background, we prefer experience administering large-scale production environments, i

MongoDB Technical Services Engineers use their exceptional problem solving and customer service skills, along with their deep technical experience, to advise customers and to solve their complex MongoDB problems. Technical Service Engineers are experts in the entire MongoDB ecosystem - database server, drivers, cloud and infrastructure. This also includes services such as Atlas (database as a service), or Cloud Manager (which helps customers with automation, backup and monitoring of their MongoDB systems). Our engineers combine their MongoDB expertise with passion, initiative, teamwork and a great sense of humor to help our customers to be successful with MongoDB. We are looking to speak to candidates who are based in Mexico City for our hybrid working model. Cool things you’ll do You'll be working alongside our largest customers, solving their complex challenges - resolving questions on architecture, performance, recovery, security, and everything in between. You'll be an expert resource on best practices in running MongoDB at scale, whatever that scale may be. You'll be an advocate for customers' needs - interfacing with our product management and development teams on their behalf. And you'll contribute to internal projects, including software development of support tools for performance, benchmarking, and diagnostics. What you need We consider all candidates with an eye for those who are self-taught, insatiably curious, and multi-faceted. The ideal candidates should have strong technical experience in one (or more) of the following areas Systems administration Distributed systems Network Administration Database architecture and administration Application Architecture Data architecture and design Performance tuning and benchmarking Extra bonus points if you have experience in one or more of Java, Python, Ruby, C, C++, C#, Javascript, node.js, Go, PHP, or Perl If you have an operations background, we prefer experience administering large-scale production environmen

Couchbase, the operational data platform for AI, empowers businesses to succeed by bringing data to life in new ways. Major market-leading companies rely on Couchbase for mission critical operational, analytical, mobile and AI workloads. Built to replace legacy infrastructure and fragmented data services, Couchbase empowers enterprises with a unified platform architected for performance, flexibility and global scale. With Couchbase, organizations bring their data to life, launching game‑changing customer experiences, exploring the limitless potential of AI, and seamlessly extending applications from the cloud to the edge and beyond. Couchbase’s AI‑ready technology and enterprise partnership model eliminate complexity and reduce total cost of ownership, enabling teams to stay agile, innovative and secure. Couchbase believes data should never slow you down, but act as the foundation for your next breakthrough. Discover why Couchbase is trusted to help the world’s biggest players scale, move fast and stay resilient, no matter what’s next on their roadmap. Visit couchbase.com and follow us on LinkedIn and X. Want to be part of our story? Apply today! AI Platform Engineering Location: Bangalore (Hybrid - in office at least 3 days/week) About the Role We are seeking an experienced and visionary technology leader to lead the development and scaling of our Operational AI platform capabilities. This role will own the strategy, architecture, delivery, and operational excellence of Couchbase AI Cloud Platform capabilities. This is a strategic leadership role at the intersection of distributed systems, cloud-native platforms, and AI. You will lead a large, multi-layered engineering organization responsible for delivering The Operational Data Platform for AI, while partnering closely with Product, Design, SRE, and Go-To-Market teams. Your leadership will directly influence company growth, customer adoption, platform reliability, and Couchbase’s competitive pos

About the Team OpenAI’s Research Program Management team partners with researchers and engineers to advance the development of increasingly capable, safe, and beneficial AI systems. We work alongside teams developing our core models, helping turn ambitious research goals into coordinated execution across model training, alignment and safety, and research infrastructure. The team also regularly collaborates with our closest cross-functional partners such as Security, Applied product and engineering, Strategy, and Scaling. About the Role As a Research Program Manager, you will embed with research teams and help drive some of the most technically complex and consequential work behind OpenAI’s model development. Depending on your focus, your work may span training, reasoning, evaluations, compute, research infrastructure, safety, model launch readiness, and governance. You will translate evolving research priorities into actionable programs, help teams navigate technical and operational tradeoffs, and keep important work moving as new issues emerge. This is a hands-on technical role: you will engage directly with research workflows, experimental results, technical systems, and engineering constraints; not simply coordinate from the sidelines. 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. You might thrive in this role if you: Have 5+ years of experience in research program management, technical program management, or related roles in fast-moving environments. Can engage substantively with researchers and engineers on topics such as model training, experimental design, model safety, evaluation methods, data workflows, compute infrastructure, or distributed systems. Are comfortable working directly with technical tools, research data, experimental results, or operational workflows to understand problems and develop practical solutions. Have a strong track record of movi

At Datadog, we're on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scale, enabling seamless collaboration and problem-solving among Dev, Ops, and Security teams globally for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. APM at Datadog is on its way to redefine how users interact with their telemetry. We are integrating intelligence directly into troubleshooting workflows to help engineers find root causes faster, navigate complex distributed systems seamlessly, and optimize application performance with minimal cognitive load. APM provides deep visibility from end-user interactions to backend services and we are now expanding this foundation with new AI-driven insights, guidance, and automation. As a Product Manager II for APM, you will work with world-class engineers, designers, and partner product teams to shape the future of Distributed Tracing, Performance Analysis, and Intelligent Troubleshooting. You will help build advanced capabilities that scale to thousands of customers and make sophisticated observability workflows accessible to every engineer, from experts to beginners. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What you will do: Develop a deep understanding of APM customers, their performance challenges, telemetry workflows, and competitors Lead conversations with design partners and strategic customers to uncover real-world performance issues, validate product assumptions, and guide solutions from early prototypes through General Availability Define and deliver the next generation of APM features with engineering and design, especially agentic on

At Datadog, we're on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scale, enabling seamless collaboration and problem-solving among Dev, Ops, and Security teams globally for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. APM at Datadog is on its way to redefine how users interact with their telemetry. We are integrating intelligence directly into troubleshooting workflows to help engineers find root causes faster, navigate complex distributed systems seamlessly, and optimize application performance with minimal cognitive load. APM provides deep visibility from end-user interactions to backend services and we are now expanding this foundation with new AI-driven insights, guidance, and automation. As a Product Manager II for APM, you will work with world-class engineers, designers, and partner product teams to shape the future of Distributed Tracing, Performance Analysis, and Intelligent Troubleshooting. You will help build advanced capabilities that scale to thousands of customers and make sophisticated observability workflows accessible to every engineer, from experts to beginners. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What you will Do: Develop a deep understanding of APM customers, their performance challenges, telemetry workflows, and competitors Lead conversations with design partners and strategic customers to uncover real-world performance issues, validate product assumptions, and guide solutions from early prototypes through General Availability Define and deliver the next generation of APM features with engineering and design, especially age

We are seeking an experienced Quantitative Developer to join our Markets Quantitative Analytics team, partnering closely with Quantitative Analysts, Traders, and Technology professionals to build the next generation of pricing, risk, and analytics platforms. This is a hands-on technical role for a highly skilled software engineer with a passion for quantitative finance. You will be responsible for designing and delivering high-performance, scalable solutions that support front office trading businesses across asset classes. The role offers the opportunity to work on complex quantitative challenges, modern engineering practices, and large-scale distributed systems while helping shape the strategic direction of Citi's quantitative technology platform. Successful candidates will combine strong software engineering expertise with an understanding of quantitative methodologies and financial markets, translating sophisticated mathematical models into robust, production-grade solutions. Key Responsibilities Design, develop, and maintain high-performance pricing, risk, and analytics libraries used across Global Markets. Partner with Quantitative Analysts to transform research models and prototypes into scalable, production-quality software. Build and optimize quantitative applications using modern C++ and Python, applying strong software architecture and engineering principles. Own the full software development lifecycle, including requirements gathering, design, implementation, testing, deployment, and ongoing support. Drive engineering excellence through CI/CD adoption, automated testing, code reviews, and software quality best practices. Develop and maintain market data platforms and data pipelines supporting analytics, pricing, and risk workflows. Work with infrastructure teams to leverage distributed computing, cloud technologies, and scalable arc

As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r

As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r

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 . As a Solutions Architect on the Sales, Trading and Prime team, you'll help scale our B2B products by bridging technical field engagement with hands-on software development. You'll work directly with customers, from startups to large institutions, as a trusted technical advisor while contributing to open source projects and extending Coinbase's core products to unlock strategic client opportunities. This role involves substantial coding, and candidates must be actively developing and delivering software in their current role. What you’ll do: Partner with customers as a trusted technical advisor, guiding them in building on Coinbase services and APIs and deepening relationships as they scale. Collaborate with sales teams to address prospect technical requirements and support deal closure. Architect distributed systems solutions for complex customer needs and build open source SDKs and reference implementations. Lead customer implementations end-to-end, delivering technical presentations, resolving roadblocks, and partnering with support teams to ensure success. Drive collaboration with product and engineering teams to extend core capabilities for strategic client opportunities. Required skills and experience: Degree in computer science and 3+ years of software engineering experience, including expert-level proficiency with REST and WebSocket APIs and production experie

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. Snowflake is building the platform that teams rely on to make data useful, reliable, and ready for the age of AI. As customers shift from batch analytics to real-time systems and intelligent applications, streaming is becoming core to how data is produced, consumed, and acted upon. We are seeking a Senior Product Manager to lead Snowflake’s Streaming Platform. This role is at the center of the real-time data shift, defining how data in motion becomes data that teams can trust, analyze, and use to power AI-driven workflows. Streaming is the backbone for modern applications, operational analytics, and Agent to Agent pipelines. If you are passionate about distributed systems, care about craft, and want to work on problems that matter at massive scale, this is a rare opportunity to build something foundational. What You Will Do Product Vision: Own the product direction, strategy, and roadmap for Snowflake’s streaming capabilities. Execution: Translate complex customer problems into clear product bets and successfully shipped features. Engineering Partnership: Collaborate closely with engineering on system design, trade-offs, and execution. User Focus: Spend time with users to understand what is broken, what is missing, and what matters most. Design & GTM: Partner with desig

Own the architecture of Myntra’s new product platforms to drive business results Drive and own the architecture and design of some of the most advanced & complex software systems / products in the industry to create company wide impact Help build, mentor and coach a team of very talented Engineers, Architects, Quality engineers, System Operation Engineers and DevOps engineers in architectural and design best practices Experience in distributed systems, cloud service development, deployment and delivery Accountable for the design, for the ease of evolution, quality of the systems, performance, scaling, and availability characteristics and limitations of the systems Envision and develop the long-term architectural direction, with emphasis on platforms/ reusable components while adopting an agile delivery process. Establish structures and processes that ensure a high level of quality and reliability and extensibility of deliverables Drive the creation of next generation extensible web, mobile and fashion commerce platforms, security protocols, customisation and tools to support continuous scaling, internationalisation and platform extensions Drive code and design reviews of components / systems / products in scope and drives the architectural governance for them Set directional paths for the teams/department for adoption of new technology stacks for solving business problems Represent multiple technology domains and Myntra in external technical forums Work with product management, business stakeholders and other engineering leaders to help define mid-term, long-term roadmaps and shape business directions Initiate and deliver leadership training within the engineering organisation, including training new managers, and drive the growth of leaders to create a strong leadership bench. Qualifications & Experience 8+ years of experience in software product development Must have a degree in Computer Science o