Software Engineer Distributed Systems Salary India Jobs

At Bazaarvoice, we create smart shopping experiences. Through our expansive global network, product-passionate community & enterprise technology, we connect thousands of brands and retailers with billions of consumers. Our solutions enable brands to connect with consumers and collect valuable user-generated content, at an unprecedented scale. This content achieves global reach by leveraging our extensive and ever-expanding retail, social & search syndication network. And we make it easy for brands & retailers to gain valuable business insights from real-time consumer feedback with intuitive tools and dashboards. The result is smarter shopping: loyal customers, increased sales, and improved products. The problem we are trying to solve : Brands and retailers struggle to make real connections with consumers. It's a challenge to deliver trustworthy and inspiring content in the moments that matter most during the discovery and purchase cycle. The result? Time and money spent on content that doesn't attract new consumers, convert them, or earn their long-term loyalty. Our brand promise : closing the gap between brands and consumers. Founded in 2005, Bazaarvoice is headquartered in Austin, Texas with offices in North America, Europe, Asia and Australia. It’s official: Bazaarvoice is a Great Place to Work in the US , Australia, India, Lithuania, France, Germany and the UK! As the Lead Engineer of Portal Reports and Insights application team, your primary responsibilities will include designing and implementing distributed, fault-tolerant systems and creating high performance Reporting and Insights applications for Bazaarvoice clients that can run nearly 10k reports every week. These reports and insights are used to produce various metrics about Bazaarvoice products and programs so that their performance can be measured. Reports can also be used to simply export raw data about client's UGC like questions, answers, reviews and products, while Insights provides

Opportunity Overview: This is a unique opportunity to join a high-caliber software engineering team that is experiencing rapid growth. You’ll play a key role in building impactful healthcare technology on a modern technology stack, with a focus on our core data and AI platforms. Your work will focus on enhancing the platform's key features while also balancing scalability, reusability, and performance. As a Staff Engineer on the Application Engineering team, you’ll serve as a senior technical leader - responsible for designing and delivering high-quality, scalable software systems that power Cohere Health’s core platform. You’ll act as a multiplier, elevating the technical bar for the team, mentoring engineers, and partnering with product, data, design , clinical and payment teams to deliver solutions that meet compliance, quality, and performance standards. This role is ideal for engineers who thrive on solving complex problems in healthcare, have deep expertise in building distributed systems including data solutions, and want to influence architectural decisions for security and scale, drive cross-collaborations for alignment, establish technical standards for consistency and evolve both application and data engineering best practices at scale. What you’ll do: Technical Leadership & Architecture Define and drive the architecture of large-scale, distributed application systems across the Cohere platform. Ensure solutions are secure, performant, maintainable, and compliant with NCQA, CMS, and payer requirements. Champion platform engineering best practices in CI/CD, testing, release management, and observability. Hands-On Engineering Write clean, maintainable, and well-tested code, primarily in modern frameworks (e.g., Python, TypeScript/React, Java/Kotlin). Lead the development of core features and APIs that directly impact providers, payers, and patients. Partner with DevOps and Data teams to ensure seamless integration, scalability, and operati

About Graphcore At Graphcore, we’re building the future of AI compute. We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale. As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence . Job Summary Join our dynamic Software Infrastructure team and take a pivotal role in scaling and managing our infrastructure. You will develop essential tools and services that empower our broader software team. Your contributions will enhance the build, test, deployment, and productisation processes of our Machine Learning Software components. Work with our High-Performance Computing (HPC) AI platforms and gain invaluable experience in distributed systems The Team The Software Infrastructure team provides critical platforms and services for software development teams across the business. Our responsibilities include managing the CI platform and services, build engineering, component integration, and packaging and release systems. We operate in squads, fostering a culture of service ownership and empowerment for our engineers. We focus on long-term engineering solutions and strive to eliminate toil wherever possible. Responsibilities and Duties Develop, own, and maintain tools and services to support AI research and engineering teams Deploy and maintain services with Kubernetes and Docker Manage our Cloud Infrastructure using tools such as Terraform Candidate Profile Essential:

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. You will partner with the teams building these storage services to define SLOs, shape capacity plans, and ensure the reliability, durability, and operational safety of the storage layer that underpins Atlas. You’ll join a small, senior team of SREs as founding members of this organization, playing a crucial role in executing on a multi-year roadmap for MongoDB’s cloud storage architecture. This role can be based out of our Boston, New York City, Raleigh, Miami, Pittsburgh or remotely in the United States while physically based in an Eastern or Central time zone location. The ideal candidate should Have 6+ years of experience working on software development and operating distributed systems Proficiency in Python, Go, or a similar language Have operated or supported stateful storage or database systems at scale, and are comfortable with durability, consistency, and recovery trade-offs. Possess a customer-focused mindset Value efficiency in processes and operations Prefer automation over manual processes. We are a small team of software engineers with a strong bias towards software solutions to avoid toil Experience using and extending containerization technologies, particularly Kubernetes, to enhance application agility, optimize resource utilization, and accelerate time-to-market Expertise in cloud infrastructure platforms, including AWS, Google Cloud Platform (GCP), or Azure Understanding of Linux operating system internals and networking concepts (e.g., TCP/IP, DNS, TLS, routing) Responsibilities Work on our multi-tenant distributed storage systems, balancing long-term strategic infrastructure g

The Team 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. You will partner with the teams building these storage services to define SLOs, shape capacity plans, and ensure the reliability, durability, and operational safety of the storage layer that underpins Atlas. You’ll join a small, senior team of SREs as founding members of this organization, playing a crucial role in executing on a multi-year roadmap for MongoDB’s cloud storage architecture. This role can be based out of either our Dublin or Cork office or remotely in Ireland. The ideal candidate should Have 6+ years of experience working on software development and operating distributed systems Proficiency in Python, Go, or a similar language Have operated or supported stateful storage or database systems at scale, and are comfortable with durability, consistency, and recovery trade-offs. Possess a customer-focused mindset Value efficiency in processes and operations Prefer automation over manual processes. We are a small team of software engineers with a strong bias towards software solutions to avoid toil Experience using and extending containerization technologies, particularly Kubernetes, to enhance application agility, optimize resource utilization, and accelerate time-to-market Expertise in cloud infrastructure platforms, including AWS, Google Cloud Platform (GCP), or Azure Understanding of Linux operating system internals and networking concepts (e.g., TCP/IP, DNS, TLS, routing) Responsibilities Work on our multi-tenant distributed storage systems, balancing long-term strategic infrastructure goals with immediate engineering needs Build for reliability, making services and infrastructure avail

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. You will partner with the teams building these storage services to define SLOs, shape capacity plans, and ensure the reliability, durability, and operational safety of the storage layer that underpins Atlas. You’ll join a small, senior team of SREs as founding members of this organization, playing a crucial role in executing on a multi-year roadmap for MongoDB’s cloud storage architecture. This role can be based out of our Toronto or Montreal office or remotely in the Canada while physically based in an Eastern or Central time zone location. The ideal candidate should Have 6+ years of experience working on software development and operating distributed systems Proficiency in Python, Go, or a similar language Have operated or supported stateful storage or database systems at scale, and are comfortable with durability, consistency, and recovery trade-offs. Possess a customer-focused mindset Value efficiency in processes and operations Prefer automation over manual processes. We are a small team of software engineers with a strong bias towards software solutions to avoid toil Experience using and extending containerization technologies, particularly Kubernetes, to enhance application agility, optimize resource utilization, and accelerate time-to-market Expertise in cloud infrastructure platforms, including AWS, Google Cloud Platform (GCP), or Azure Understanding of Linux operating system internals and networking concepts (e.g., TCP/IP, DNS, TLS, routing) Responsibilities Work on our multi-tenant distributed storage systems, balancing long-term strategic infrastructure goals with immediate engineerin

About the Team The Software Engineering team is responsible for designing and building the scalable, performant, and secure backend systems that power our products—from early prototypes to large-scale deployments. We collaborate closely with product, hardware, and full-stack teams to ensure our infrastructure enables fast iteration while setting a strong foundation for long-term growth. About the Role As a Backend Engineer , you will design and build services, APIs, and infrastructure that support evolving product needs. You’ll apply a deep understanding of backend systems and maintain enough end-to-end context—from hardware to cloud—to guide technical decisions that best serve the product and team. We’re looking for engineers who thrive in fast-paced, collaborative environments and care deeply about building robust systems that scale. This role is based in San Francisco, CA . We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees. In this role, you will: Architect, build, and maintain high-performance, secure backend systems. Design APIs, data models, and infrastructure to support evolving product needs. Balance near-term development velocity with long-term maintainability and scalability. Collaborate with cross-functional teams to ensure cohesive, end-to-end solutions. You might thrive in this role if you: Have 7+ years of professional software engineering experience, with a focus on backend systems. Have a proven track record of building and scaling systems from early stage to large scale. Are proficient with Python and Go, and familiar with a range of server-side technologies. Have a strong grasp of system design, performance optimization, and security best practices. Can reason about full-stack tradeoffs from hardware through cloud infrastructure. (Nice to have) Have experience with distributed systems and cloud architectures. (Nice to have) Bring a background in instrumentation, analytics, and performanc

About the Team This team builds an AI-native predictive analytics platform that embeds ML and AI-driven insights directly into production Go-To-Market workflows — powering real-time decisions at scale. The team owns the full stack from distributed data pipelines and backend services to ML and AI-powered capabilities that ship directly to customers. We are building toward a model where AI components are first-class runtime dependencies, not bolt-on features. Agentic AI development is a core part of how we increase engineering velocity and deliver customer value. This is a team that ships daily, iterates constantly, and treats speed as a capability to be deliberately improved. The Role This is a high-ownership, builder-first Sr. Software Engineer role. You will design, build, and ship AI-integrated data systems from concept through production — owning outcomes end-to-end, including deployment, monitoring, cost, and business impact. We are seeking a candidate who views AI tooling as a fundamental force multiplier in their daily engineering process. This position is central to our transition into an AI-native function, requiring an individual capable of making decisive, pragmatic architectural choices on reversible matters to maintain momentum. We need an experienced builder of production-grade, data-centric systems who is obsessed with delivering customer value and possesses a deep, curious enthusiasm for the transformative potential of AI. What You Will Build AI-Native Systems Development. Design, build, and own scalable data and ML pipelines, backend services, and AI-powered capabilities that are part of the platform's production decision-making layer. AI and ML components are runtime dependencies in this role — not research projects or experiments. Candidates will have strong back end and data engineering skills to thrive in this space. Daily Shipping. Decompose complex work into safely mergeable increments and ship them daily. Treat large, multi-day pull requ

About the Team pAGI Infra team builds and operates the systems that make large-scale model training and evaluation reliable, efficient, and easy to run. Our work spans distributed training infrastructure, inference and grading platforms, compute scheduling, and research tooling. We partner closely with researchers and engineering teams to turn new research needs into dependable infrastructure, improve GPU efficiency, and shorten the path from an experiment to a validated model. About the Role We’re looking for an AI Systems Engineer to help scale the infrastructure behind our training and evaluation workflows. You’ll own projects from identifying bottlenecks and designing solutions through deployment and operation. The work combines distributed systems engineering, performance optimization, and close collaboration with researchers. You might build a shared grading service, improve resource allocation across workloads, or bring a new training stack into production — directly improving how quickly and reliably research moves forward. In this role, you will: Build and operate infrastructure for large-scale training and evaluation, improving reliability, throughput, and resource efficiency. Develop shared inference and grading platforms with automated capacity management, health monitoring, and visibility into performance. Improve compute scheduling and resource allocation to reduce idle GPU time and help workloads recover quickly from failures. Diagnose bottlenecks across training, inference, and orchestration, and work across teams to improve end-to-end performance. Build self-service tools, automated validation, and observability that help researchers launch experiments, diagnose issues, and compare results with less manual intervention. You might thrive in this role if you: Are excited about the potential of personal AGI and want to build the infrastructure that enables it. Have strong software engineering fundamentals and experience building or operating large-scal

The worldwide data management software market is massive (IDC forecasts it to be $138 billion by 2026). At MongoDB, we are transforming industries and empowering developers to build amazing apps that people use every day. We are the leading modern data platform and the first database provider to IPO in over 20 years. Join our team and be at the center of innovation and creativity. MongoDB is seeking a Sr. Staff Software Engineer to join the Atlas Core Data Services organization. The organization is responsible for building MongoDB Atlas, our database as a service offering and fastest growing product, along with the API Platform and Developer Tools. Atlas allows users to deploy fault-tolerant, secure, globally distributed MongoDB clusters in just minutes. The Atlas Core Data Services organization builds the software that manages the Atlas cluster infrastructure hosted on the three major cloud providers (AWS, Azure, and GCP), as well as the software that manages the MongoDB database hosted on that infrastructure. We are constantly challenged to design features that ensure Atlas clusters are secure, available, durable, and performant while running large-scale, critical workloads. The Sr. Staff Engineer in this role will drive innovation across the organization and the company, setting technical standards and direction that enable future growth and velocity. We are looking for engineers with the experience and high standards needed to lead at that scale. Our organization champions a strong culture of inclusivity, diversity, and collaboration. If you want to be a deeply technical leader on a collaborative team that applies systems expertise to build the foundational infrastructure of a popular database, join us. Let's build a faster, more reliable, and highly scalable database platform together. We are looking to speak to candidates who are based in Dublin for our hybrid working model. Responsibilities Define standards and vision for the mission-critical Atlas SaaS data

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 The Customer Engineer will play a crucial role in the customers’ post-sale journey - helping them to onboard, adopt and grow on Anyscale, troubleshooting and resolving open customer tickets and driving consumption. Anyscale is an ever evolving platform and hence will require close co-ordination with our engineering teams to debug complex issues. This is an exciting role for those who are technically curious and passionate about ML/AI, LLM, vLLM and the role of AI in next generation applications. It’s an opportunity to make a significant impact in a collaborative, fast-paced environment while building a new segment in this space. In this role, you’ll be able to Resolve customer issues and help in their successful adoption of Anyscale platform Be a technical advisor, and internal champion for our key customers Own customer issues end-to-end, from troubleshooting, triaging, escalations and eventual resolution Participate in our follow-the-sun customer support model to ensure continuity in resolving high priority tickets Keep track of open customer bugs and feature requests to influence prioritization and provide timely customer updates upon resolution Contribute towards improvement of internal tools an

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: As a Forward Deployed Engineer at Anyscale, you will partner directly with our most strategic customers, including Spanish-speaking customers across Latin America and other regions, to ensure they achieve meaningful business outcomes with Ray and the Anyscale platform. Embedded within customer teams, you’ll act as a trusted advisor, aligning technical solutions with customer priorities, accelerating time-to-value, and driving adoption at scale. You’ll work across customer organizations — from technical leadership to individual contributors — to scope and deliver impactful solutions. By connecting insights from the field back to our product and engineering teams, you’ll help shape Anyscale’s roadmap and ensure we remain focused on solving our customers’ most critical challenges. In this role, you will: Work onsite with key customers to lead proof-of-value engagements, deployments, and enterprise adoption Translate business objectives into technical solutions that demonstrate clear ROI and strategic impact Build and deliver high-impact demos, reference architectures, and enablement programs tailored to customer needs Act as a trusted advisor across all levels of the organization, ensuring confidence in Anyscale and

A World-Changing Company Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more. The Role Forward Deployed Infrastructure Engineers (FDIEs) build, operate, and maintain the infrastructure that powers Palantir’s platforms and production deployments. As an FDIE intern, you’ll work alongside full-time FDIEs to deploy and operate Palantir software across real production environments, automate manual processes, and develop novel solutions to infrastructure challenges using tools like Foundry and Apollo. Every day looks different — you might be debugging a distributed systems issue, building automation to replace a manual runbook, or designing infrastructure improvements that scale across multiple deployments. You’ll be treated as a full member of the team, with real ownership over the work you take on. Core Responsibilities As an FDIE intern, your responsibilities look similar to those at a small startup, with the resources, stability, and mentorship of an established tech company. You’ll work in small teams with minimal supervision and own end-to-end execution of real infrastructure projects. Your day might span discussing systems architecture with fellow engineers, debugging a production issue, building automation to eliminate a manual process, or deploying new Palantir products across production environments. FDIE interns are treated just like full-time engineers, with significant freedom and ownership over their work. Specifically, you can expect to: Deploy and operate Palantir software across production environments, including monitoring, alerting, configuration management, and upgrades Debug, improve, and optimize Palantir’s services and infra

A World-Changing Company Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more. The Role Forward Deployed Infrastructure Engineers (FDIEs) build, operate, and maintain the infrastructure that powers Palantir’s platforms and production deployments. As an FDIE intern, you’ll work alongside full-time FDIEs to deploy and operate Palantir software across real production environments, automate manual processes, and develop novel solutions to infrastructure challenges using tools like Foundry and Apollo. Every day looks different — you might be debugging a distributed systems issue, building automation to replace a manual runbook, or designing infrastructure improvements that scale across multiple deployments. You’ll be treated as a full member of the team, with real ownership over the work you take on. Core Responsibilities As an FDIE intern, your responsibilities look similar to those at a small startup, with the resources, stability, and mentorship of an established tech company. You’ll work in small teams with minimal supervision and own end-to-end execution of real infrastructure projects. Your day might span discussing systems architecture with fellow engineers, debugging a production issue, building automation to eliminate a manual process, or deploying new Palantir products across production environments. FDIE interns are treated just like full-time engineers, with significant freedom and ownership over their work. Specifically, you can expect to: Deploy and operate Palantir software across production environments, including monitoring, alerting, configuration management, and upgrades Debug, improve, and optimize Palantir’s services and infra

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