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Software Engineer Distributed Systems Salary India Jobs

6,428 active opportunities · Updated for October 2026

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

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

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M
Mongodb
📍 San Francisco• Full-time• From $106K/yr
1mo ago

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

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SA
Scale AI
📍 San Francisco• Full-time• From $180K/yr
14 days ago

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

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M
Mongodb
📍 New York City; United States• Full-time• From $106K/yr
1mo ago

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

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M
Mongodb
📍 Alberta• Full-time• From C$122K/yr
1mo ago

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

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M
Mongodb
📍 Toronto• Full-time• From C$137K/yr
1mo ago

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

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M
Mongodb
📍 New York City• Full-time• From $126K/yr
1mo ago

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

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V
Vercel
📍 San Francisco• Hybrid
8 days ago

About Vercel: Vercel is the agentic infrastructure company, freeing people and agents to ship what's next. For more than a decade we've helped builders move from idea to production with speed, security, and exceptional developer experience. Now we're scaling our products for both agents and people to ship and run software, built in the open and trusted by OpenAI, PayPal, Ramp, Supreme, and millions of developers worldwide. About the Role: The Scheduled Tasks team builds the platform primitives that let applications and agents run work now, later, or for a long time. We own Vercel Workflows, Queues, and Cron: the systems developers use to build long-running, event-driven, and scheduled applications. You will join a team working at the intersection of developer experience and distributed systems. Together, we are building and scaling the products that make it straightforward for developers to coordinate background work, move messages between services, and schedule work with confidence. You will collaborate closely with engineers across Vercel to make these powerful capabilities feel simple, composable, and native to the platform. What You Will Do: Design, build, and operate platform capabilities across Workflows, Queues, and Cron. Help developers build applications and agents that coordinate background, event-driven, and scheduled work. Build APIs, SDKs, and tooling that make it easy to define, run, and manage durable work at scale. Work on the distributed-systems foundations behind scheduling, message delivery, execution, retries, and state. Partner with product, developer experience, and infrastructure teams to turn customer needs into clear, useful developer primitives. Raise the engineering bar through thoughtful design reviews, well-tested code, production ownership, and clear technical communication. Engage with developers and the open-source community to understand where background jobs, queues, and scheduling create friction—and use that feedback to improve th

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M
8 days ago

Enterprise Advanced is a distributed team across Europe and India that builds the software running MongoDB on any infrastructure, at global scale — from on-prem data centers to private cloud. You'll work primarily on Ops Manager and Automation, the systems that let customers deploy fault-tolerant, globally distributed MongoDB clusters in minutes. Our software manages some of the largest self-managed MongoDB deployments in the world, with production clusters running hundreds of shards and nodes under a single deployment. The main focus of this team is to adapt our software to manage MongoDB clusters which are deployed in data centers or private cloud platforms. You will work on the core functionality for all of our products, mainly on the Ops Manager , and Automation products. Our team's end users are some of the largest businesses in the world, deploying massive clusters and processing huge amounts of data. This role is based in our Gurgaon office, and can work in a hybrid fashion. This role will report to the Senior Engineering Manager also based in our Gurgaon office. What you’ll do Design, implement, test, and release features for Ops Manager Own end-to-end delivery of complex projects, from design through incremental shipping Troubleshoot and resolve issues surfaced in customer deployments running at scale Apply engineering judgment and MongoDB's core values across planning, design, and code review A great fit for this role will be You enjoy distributed-systems problems; consistency, fault tolerance, and scale are the daily reality, not edge cases People who like ambiguity and are comfortable defining their own approach with guidance, not step-by-step instruction You're flexible! You're willing to take on a wide variety of responsibilities, learning as you go You're a self-starter! You're comfortable organizing your own time, acting on feedback and prioritizing with guidance from senior members of your team Requirements 4+ years experience with a language

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O
OpenAI
📍 San Francisco• Full-time
1mo ago

About the Team The GPT Infrastructure team builds systems that turn advances in model inference and optimization into reliable production capabilities. We enable OpenAI workloads to be qualified and optimized across new accelerator platforms without requiring a one-off port and tuning effort for every hardware target. Our work spans distributed systems, model execution, compilers and runtimes, performance engineering, secure partner integrations, evaluation systems, and developer tooling. We build the infrastructure that makes optimization workflows automated, reproducible, and trustworthy. About the Role We are seeking a software engineer to help build the platform that qualifies and optimizes inference workloads across heterogeneous compute environments. You will develop both OpenAI-hosted services and secure partner-side software for running long-lived optimization workflows. These workflows generate candidate kernels, runtime configurations, and serving-stack changes; compile and execute them on target hardware; verify their correctness; measure their performance; and use the results to guide further optimization. You will work across model architecture, distributed execution, compilers, runtimes, networking, and accelerator systems. A central part of the role is turning research prototypes and one-off hardware bring-up efforts into reliable, reusable infrastructure with clear contracts, reproducible results, strong observability, and well-defined security boundaries. Key Responsibilities Design, build, and operate APIs and control-plane services for long-running workload qualification and optimization campaigns, including scheduling, retries, checkpointing, resource budgets, and observability. Build secure partner-side execution and evaluation software that can compile, run, verify, profile, and benchmark candidate artifacts on accelerator hardware. Integrate model workloads, hardware profiles, compiler toolchains, runtimes, serving engines, and distributed-exe

pythonawslinux
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T-
14 days ago

About the Role: Tubi's content platform is the engine behind one of the largest free streaming services in the world. Every play, every deal, every creator, every frame of video flows through systems CPE owns, and the surface area is enormous. Distributed services running on the hottest path of Tubi's traffic. Video pipelines processing one of the largest workloads in streaming. Workflow engines automating the operations that used to consume entire teams. Creator-facing products turning a back-office process into a real platform. And on top of all of it, an AI-native rebuild of the CMS that most companies aren't willing to attempt. This isn't a single-domain role. It's a platform where backend, frontend, video, infrastructure, and applied AI all collide at the scale where decisions actually matter, where an architectural choice ripples across millions of titles and billions of requests, and where the difference between "good enough" and "great" shows up in revenue. We're looking for builders who want to range across domains — backend one quarter, frontend the next, applied AI the one after that — and who want their work to be felt: by viewers when a title plays instantly, by creators when they go live the same day, by Content Ops when a workflow runs itself, and by the business when the platform stops being a cost center and starts being a force multiplier. The infrastructure is already there. The mandate is already there. What's missing is the people who want to build the thing, not talk about it. Come build it. 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: You'll work on systems that sit at the heart of Tubi's business, where the content pipeline meets the viewer, the creator, and increasingly, the AI agent. The work spans the full stack of a modern content platform: distributed services, video infrastructure, workflow automation, and applied AI, all running at

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B
1mo ago

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE Baseten’s Inference Stack team builds the distributed runtime that powers large-scale LLM inference across our platform. We operate at the intersection of distributed systems, model performance, infrastructure, and developer experience. We enable customers to deploy and operate cutting-edge LLM models with industry-leading performance, scalability, reliability, and ease of use. As a Software Engineer on the Inference Stack team, you’ll work across the stack - from the developer experience customers use to deploy models, the libraries used for features like tool calling and reasoning, all the way down to the systems we use to orchestrate deployments in Kubernetes and route traffic efficiently. This is an ideal role for engineers who enjoy owning systems in production, solving hard integration problems, and making complex infrastructure simple and reliable for users. EXAMPLE INITIATIVES Blog Posts https://www.baseten.co/blog/nvidia-dynamo-day-baseten-inference-stack/ https://www.baseten.co/blog/how-baseten-achieved-2x-faster-inference-with-nvidia-dynamo/ https://www.baseten.co/blog/how-baseten-multi-cloud-capacity-management-mcm-powers-cloud-self-hosted-and-hybr/#comparing-deployment-options-cloud-vs-self-hosted-vs-hybrid RESPONSIBILITIES Develop infrastructure and orchestration systems for deploying and managing large-scale distributed LLM inference Work across the stack, from customer-facing features to low-le

kubernetesci/cdrest
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O
1mo ago

About the Team Our London-based team builds the backend systems that help ChatGPT scale reliably. We work on infrastructure close to the product, partnering with engineering teams to improve the performance, resilience, and operability of critical user-facing systems. Our work combines backend software engineering with distributed systems and production reliability. We build shared capabilities, improve high-traffic workflows, and make it easier to introduce new product functionality without compromising performance or availability. About the Role This role is for software engineers who want to build and evolve backend systems operating at significant scale. You’ll write production code, design shared infrastructure, and solve technical challenges involving performance, distributed systems, and system reliability. You’ll also own how those systems behave in production: how changes are rolled out, how issues are detected and diagnosed, and how recurring operational problems can be addressed through better software and system design. This is a strong fit for backend engineers who enjoy complex systems problems and want a direct connection between the infrastructure they build and the experience of ChatGPT users. In this role, you will: Design, build, and maintain backend systems supporting high-traffic ChatGPT experiences. Develop shared services, APIs, and infrastructure that help product teams build and launch new capabilities safely. Improve the performance, scalability, and efficiency of production systems as usage and product complexity grow. Build and improve systems for asynchronous processing and other large-scale backend workloads. Lead architectural improvements and infrastructure migrations while maintaining correctness, compatibility, and safe rollout and rollback. Strengthen monitoring, alerting, and diagnostics to detect problems early and reduce customer impact. Participate in on-call, incident response, and root-cause analysis, and turn operational lea

awsrestai
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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 seeking a Staff Software Engineer to lead the technical vision for our Infrastructure team. As a Staff Engineer, you will be responsible for the architectural evolution of our control plane and data plane, ensuring that our "infinite laptop" vision scales to meet the most demanding distributed AI workloads in the world. You will act as a force multiplier, setting the standards for Kubernetes-based cloud-native infrastructure while mentoring engineers and driving cross-functional alignment across the Ray open-source community and our proprietary product teams. Key Responsibilities Architectural Leadership: Define and drive the multi-year technical roadmap for services that orchestrate Ray clusters across diverse cloud and on-premises environments. Systemic Optimization: Lead the design and optimization of high-performance control plane components specifically tailored for large-scale, heterogeneous AI/ML workloads. Platform Reliability: Establish the organization-wide standards for the reliability, scalability, and observability of Anyscale-managed infrastructure. Strategic Integration: Direct the long-term strategy for accelerator integration (GPUs, TPUs) and container management to ens

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M
Mongodb
📍 New York City; United States• Full-time• From $126K/yr
1mo ago

MongoDB’s Storage Layer Services (SLS) team is re-architecting the MongoDB cloud storage layer and sits at the heart of our next-generation cloud storage architecture. This relatively new team is building performant, multi-tenant distributed storage services that both enhance today’s Atlas storage stack and enable more customer workloads to run more efficiently. We are looking for a talented Senior Software Engineer to join our team as we execute on a multi-year roadmap and prepare to launch and rapidly scale services that handle petabytes of data. Come do some of the most interesting work of your career as we Think Big and Go Far for our customers! This role can be based out of our New York City office (hybrid working model) or remotely in the North America region. What you’ll do Design, build, and operate control plane services powering an elastic and multi-tenant storage layer for thousands of database instances. Solve problems around maintaining high availability and performance during load spikes, hardware failures, cloud provider outages, and other disruptions. Contribute to a culture of operational excellence through dashboards, playbooks, and on-call improvements. Lead complex technical projects from planning through successful deployment with clear stakeholder updates. Partner closely with peers across database, cloud, and infrastructure engineering teams as well as project management to investigate incidents and develop long-term roadmaps. Mentor junior engineers and foster a collaborative team environment. We’re looking for someone with 5+ years of professional software development experience building, deploying, and operating multi-tenant cloud services with a focus on operational excellence. Experience with large backend/compiled codebases, such as Rust or C/C++. Experience with containerization and orchestration platforms (e.g. Kubernetes). Experience with observability tooling (e.g. time series metrics, dashboards). Experience with distributed systems

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