Application Developer Jobs

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Backend Engineer on the Gitaly team, you’ll help build GitLab’s Git data storage tier, a standalone product that provides reliable, secure, and fast access to Git repositories through application programming interfaces (APIs) and storage operations. You’ll work at the boundary between GitLab and Git to make repository access performant and dependable for GitLab.com , self-managed customers, and GitLab Dedicated. Our work spans distributed storage, repository management, high availability, performance, observability, and operational excellence. We’re currently building the next generation of source co

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: As a Site Reliability Engineer, you will play a crucial role in ensuring the smooth operation of all user-facing services and other Anyscale production systems. Anyscale values diversity and inclusion, and we encourage applications from individuals of all backgrounds. This includes processes for provisioning, negotiating prices, managing costs, seeing opportunities for teams to reduce wastage by finding applications across the company. You will apply sound engineering principles, operational discipline, and mature automation to our environments and the Anyscale codebase as we scale. As part of this role, you will: Develop a unified perspective on how cloud components are utilized across the company, taking into account diverse needs and requirements. Ensure that deployment methodologies align with the company's reliability goals. Build systems that promote understanding of production environments, facilitating quick identification of issues through robust observability infrastructure for metrics, logging, and tracing. Create monitoring and alerting systems at different levels, enabling teams to easily contribute and enhance the overall monitoring capabilities. Establish testing infrastructure to s

The worldwide data management software market is massive. 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 forefront of innovation and creativity. MongoDB is seeking a Software Engineer 3 to join the Atlas Clusters Platform team. The team is responsible for building MongoDB Atlas, our database as a service offering and fastest growing product. Atlas allows users to deploy fault-tolerant, secure, globally distributed MongoDB clusters in just minutes. The Atlas Clusters Platform team develops the foundational orchestration platform behind MongoDB Atlas. Our systems drive cluster planning and execution, evolve the Atlas control plane toward service-oriented architecture, and provide critical infrastructure that help Atlas run safely and efficiently across cloud environments. We are looking to speak to candidates who are based in New York City for our hybrid working model. What you’ll do Build and design new features for MongoDB Atlas Contribute to and lead complex technical projects Work closely with product and design teams, considering the user’s perspective while building technical solutions Work with customers and support engineers to fix issues Collaborate with team members to develop our codebase, best practices, and design principles Learn from and mentor other team members We’re looking for someone who Has at least 3 years of professional software development experience Is skilled at writing large-scale, distributed backend systems in a compiled language (Java, C#, Go, etc.) Is comfortable working across the stack of a modern web application (e.g. React, TypeScript, Kubernetes) Has experience with at least one major cloud provider technology (AWS, Azure, GCP) Has led the launch of a new feature and maintained it in production Is eager to solve tough problems Has excellent

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Backend Engineer on the Gitaly team, you’ll help build GitLab’s Git data storage tier, a standalone product that provides reliable, secure, and fast access to Git repositories through application programming interfaces (APIs) and storage operations. You’ll work at the boundary between GitLab and Git to make repository access performant and dependable for GitLab.com , self-managed customers, and GitLab Dedicated. Our work spans distributed storage, repository management, high availability, performance, observability, and operational excellence. We’re currently building the next generation of source co

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Fullstack Engineer on the Duo Client SDK team at GitLab, you'll build the shared foundation for every GitLab Duo client. Today, the logic that powers Duo in editors lives inside the GitLab Language Server. We're extracting it into a true software development kit (SDK): a set of well-versioned TypeScript packages that editor extensions, our web-based Duo Chat on GitLab.com, and eventually external applications can use. You'll work in TypeScript across frontend and backend systems. You'll design the SDK's Node.js core and public application programming interface (API), and work in the clients that use

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 Ray Data Team: Ray Data is Python-native data processing engine that is a one stop shop for all AI data processing needs. Ray Data provides performant, first-class integration with cutting edge AI frameworks using both multi-modal and structured data. The Ray Data team currently develops and maintains Ray Data . We are a team of engineers passionate about building a Data processing engine which is a one-stop shop for all of your ML/AI needs. We are looking for exceptional engineers to build, optimize, and scale Ray for modern and increasingly complex AI workloads. As part of this role, you will: Improve the performance of Ray Data and multi-modal batch inference use cases. Ensure efficient scaling across different stages of the Data pipeline in a heterogeneous environment. Building data loading solutions for production training workloads. Focus on stability and fault tolerance at high scale Working with customers and new age AI native companies in scaling their AI workloads. We'd love to hear from you if have: At least 3-4 years of relevant work experience Solid background in building scalable and fault-tolerant distributed systems Experience with data processing, database internals. Passionate about large

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. Role Summary As a Social Media Support Specialist, you are at the forefront of helping developers create while managing our social media presence and community interactions. You'll assist developers with complex technical issues, billing inquiries, account management, and product usage questions across multiple channels including X (Twitter), LinkedIn, Reddit, Apple/Google Play stores, and other relevant platforms. You will help bubble up what is important to Replit's engineering and Product teams, and what needs improvement to your own team, while also serving as a key voice in our social media community engagement. We use tools like Zendesk, Sprout Social, Linear, Slack, Stripe, Orb, Notion, and Replit itself to get the job done, alongside social media management platforms for X, LinkedIn, and Reddit. You will work on a small, global team of support specialists and engineers united by Replit's mission to make the next billion software creators. Together, you'll ensure developers worldwide have the support they need to bring their ideas to life. In this role you will… Work directly with Replit customers via support tickets and social media accounts to solve account, billing, and product issues Manage and respond to customer inquiries and community discussions on X (Twitter), LinkedIn, Reddit, and Apple/Google Play stores, with the possibility of expanding coverage to additional platforms as we grow Monitor social media channels for product feedback, technical issues, and community sentiment Manage escalations from social media channels and coordinate with appropriate internal teams to ensure timely resolution Collaborate with the rest of the Support team in telling the story of our users to the rest of Replit Work cro

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. Role Summary As a Social Media Support Specialist, you are at the forefront of helping developers create while managing our social media presence and community interactions. You'll assist developers with complex technical issues, billing inquiries, account management, and product usage questions across multiple channels including X (Twitter), LinkedIn, Reddit, Apple/Google Play stores, and other relevant platforms. You will help bubble up what is important to Replit's engineering and Product teams, and what needs improvement to your own team, while also serving as a key voice in our social media community engagement. We use tools like Zendesk, Sprout Social, Linear, Slack, Stripe, Orb, Notion, and Replit itself to get the job done, alongside social media management platforms for X, LinkedIn, and Reddit. You will work on a small, global team of support specialists and engineers united by Replit's mission to make the next billion software creators. Together, you'll ensure developers worldwide have the support they need to bring their ideas to life. In this role you will… Work directly with Replit customers via support tickets and social media accounts to solve account, billing, and product issues Manage and respond to customer inquiries and community discussions on X (Twitter), LinkedIn, Reddit, and Apple/Google Play stores, with the possibility of expanding coverage to additional platforms as we grow Monitor social media channels for product feedback, technical issues, and community sentiment Manage escalations from social media channels and coordinate with appropriate internal teams to ensure timely resolution Collaborate with the rest of the Support team in telling the story of our users to the rest of Replit Work cro

About the Team The Applied AI Engineering team is responsible for ensuring the safe and effective deployment of Generative AI applications for developers and startups. We act as a trusted advisor and thought partner for our customers, working to build an effective backlog of GenAI use cases for their industry and drive them to production through strong technical guidance. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to late-stage startups. About the Role We are seeking a technically proficient, business-minded Applied AI Engineer to help push the frontier of advanced AI with our strategic startup customers. You'll work with some of the most exciting AI startups in the world, guiding them through ideation, development, delivery, and scaling to accelerate and maximize the value of what they build on our platform. You will have the opportunity to work on the most novel and creative use cases being built on our API, serving as a critical partner in collecting and delivering high-fidelity product and model feedback internally. You will collaborate closely with Sales, Solutions Engineering, Applied Research, and Product teams, and you will report to the Startups Applied AI Lead. This role is based in our Tokyo, Japan office. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Partner closely with strategic startup customers as their technical thought partner to build novel applications on our API, helping them rapidly move from ideation to scale. Provide proactive guidance to maximize business impact and accelerate application development. Experiment and prototype alongside customers, demonstrating practical use cases. Contribute to open-source resources and scale the function by sharing knowledge, codifying best practices, and publishing useful resources. Synthesize and deliver valuable feedback to the Product and Research teams. Build

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 Software Engineer to join the Platform and 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 team, we build the scalable, secure, and robust backbone that enables this vision, ensuring that our "infinite laptop" vision scales to meet the most demanding distributed AI workloads in the world. 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 Software Engineer 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-impa

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 an experienced and hands-on engineering leader to lead our Customer Engineering team. This is a critical leadership role within our Go-To-Market organization, responsible for delivering exceptional technical support while helping ensure customer experiences directly influence the evolution of our platform. You will lead a highly technical team responsible for supporting customers running production AI workloads on Anyscale. Your team will resolve complex technical issues, manage customer escalations, and partner closely with Product and Engineering to ensure customer feedback is translated into meaningful product improvements. Success in this role requires balancing operational excellence with strong technical leadership. Beyond resolving individual customer issues, you will help the team identify recurring patterns, improve support workflows, expand customer self-service, and leverage automation, diagnostics, and engineering best practices to improve both the customer experience and the product over time. As opportunities arise, your team may also contribute tooling, documentation, automation, or occasional product fixes that help eliminate recurring sources of customer fri

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 Ray Data Team: Ray Data is Python-native data processing engine that is a one stop shop for all AI data processing needs. Ray Data provides performant, first-class integration with cutting edge AI frameworks using both multi-modal and structured data. The Ray Data team currently develops and maintains Ray Data . We are a team of engineers passionate about building a Data processing engine which is a one-stop shop for all of your ML/AI needs. We are looking for exceptional engineers to build, optimize, and scale Ray for modern and increasingly complex AI workloads. As part of this role, you will: Improve the performance of Ray Data and multi-modal batch inference use cases. Ensure efficient scaling across different stages of the Data pipeline in a heterogeneous environment. Building data loading solutions for production training workloads. Focus on stability and fault tolerance at high scale Working with customers and new age AI native companies in scaling their AI workloads. We'd love to hear from you if have: At least 3-4 years of relevant work experience Solid background in building scalable and fault-tolerant distributed systems Experience with data processing, database internals. Passionate about large

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 As a Distributed LLM Inference Engineer, you will help systems and optimizations that push the boundaries of performance for inference at large scale. This is an incredibly critical role to Anyscale as it allows us to achieve a market leading position for AI infrastructure. As part of this role, you will Iterate very quickly with product teams to ship the end to end solutions for Batch and Online inference at high scale which will be used by open-source Ray users and customers of Anyscale Work across the stack integrating Ray Data and LLM engine providing optimizations achieving low cost solutions for large scale ML inference Integrate with Open source software like vLLM, work closely with the community to adopt these techniques in Anyscale solutions, and also contribute improvements to open source Follow the latest state-of-the-art in the open source and the research community, implementing and extending best practices We'd love to hear from you if you have Familiarity with running ML inference at large scale with high throughput and low latency Familiarity with deep learning and deep learning frameworks (e.g. PyTorch) Solid understanding of distributed systems, ML inference challenges Bonus points

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 Ray aims to provide a universal API for building distributed applications. To achieve this goal requires a distributed system with high levels of performance and reliability. We're looking for engineers with systems software experience that are interested in contributing to the Ray backend. About the Ray Core Team The Ray Core team develops and maintains the Ray C++ backend (e.g., distributed scheduler, language runtime integration, I/O and memory subsystems). We are responsible for the reliability, scalability, and performance of Ray as well as ensuring that Ray provides the right feature set to support higher level libraries and use cases. The team works on a balance of new features / distributed libraries, test infra improvements, debugging, and longer-term architectural improvements to Ray. A snapshot of projects you can work on: Optimizing performance of large-scale workloads on Ray Stability and stress testing infrastructure Improving fault tolerance (HA) As part of this role, you will: Leading cross-team projects while mentoring junior team members Develop high quality open source software to simplify distributed programming (Ray) Identify, implement, and evaluate architectural improvements

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: Ray aims to provide a universal API for building distributed applications (e.g. a machine learning pipeline of feature engineering, model training, and evaluation). Data is usually a core element connecting these different stages, and therefore plays a critical role in Ray’s usability, performance, and stability. We are looking for strong engineers to build, optimize, and scale Ray’s Datasets library and data processing capabilities in general. About the Ray Data team: The Ray Data team currently develops and maintains the Ray Datasets library, which is already powering critical production use cases (e.g. large scale data compaction at Amazon , and ML pipeline at Alibaba ). Ray Datasets is a Python library built on top of Apache Arrow and Ray Core (Ray’s C++ backend), and the Ray Data team interacts closely with Ray Core components including the scheduler and the memory & I/O subsystems. The Ray Data team also works closely with Ray’s ML libraries including Train, RLlib, and Serve. A snapshot of projects you will work on: - Performance of Ray Datasets at large scale (leveraging Arrow primitives, optimizing Ray object manager, etc.) - Integration with ML training and data sources - Stability an