Software Engineer Distributed Systems Jobs

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: Running machine learning (ML) algorithms at our scale often requires solving novel systems problems. As a Performance Engineer, you'll be responsible for identifying these problems, and then developing systems that optimize the throughput and robustness of our largest distributed systems. Strong candidates here will have a track record of solving large-scale systems problems and will be excited to grow to become an expert in ML also. You may be a good fit if you: Have significant software engineering or machine learning experience, particularly at supercomputing scale Are results-oriented, with a bias towards flexibility and impact Pick up slack, even if it goes outside your job description Enjoy pair programming (we love to pair!) Want to learn more about machine learning research Care about the societal impacts of your work Strong candidates may also have experience with: High performance, large-scale ML systems GPU/Accelerator programming ML framework internals OS internals Language modeling with transformers Representative projects: Implement low-latency high-throughput sampling for large language models Implement GPU kernels to adapt our models to low-precision inference Write a custom load-balancing algorithm to optimize serving efficiency Build quantitative models of system performance Design and implement a fault-tolerant distributed system running with a complex network topology Debug kernel-level network latency spikes in a containerized environment Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. Fo

About the Role As a Senior Infrastructure Engineer on the Compute & Storage Platform team in Toast, you will design, build, and operate the foundational distributed systems powering the Toast platform as the company expands into further international markets and broadens its product offerings to encompass retail shopping. You will bridge the gap between core infrastructure and cutting-edge product development—building low-latency state and storage systems, scalable compute clusters, and high-throughput streaming pipelines. Your work will directly enable Toast product delivery across our Product Development Life Cycle (PDLC). For this role it is a requirement that you 5+ years of industry experience Key Responsibilities Online Databases and Storage: Architect, deploy, and manage low-latency, highly available storage solutions (RDS Postgres and Aurora Postgres; DynamoDB; OpenSearch; S3) to power applications across the Toast product ecosystem. High Availability & Realtime Performance: Ensure sub-second end-user latency, near-zero-downtime reliability, and high throughput across storage engines to support Toast's products across POS, phone, computer, drive-thru, and kiosk interfaces. Infrastructure for AI-Driven PDLC: Automate infrastructure provisioning and compute pipelines. Cost Optimization & Performance Engineering: Right-size compute/storage resources, implement auto-scaling policies, and manage AWS infrastructure costs without compromising platform reliability or latency SLAs. Required Qualifications 1. Core Infrastructure & Automation Cloud & Infrastructure as Code: Hands-on experience building and managing scalable cloud infrastructure on AWS using Infrastructure as Code (Terraform, CloudFormation, etc.). Software Development: Fluency in Python , Go , or a similar language for infrastructure automation, tooling, or backend development. 2. Storage & Compute Operations Databases: Deep experience operating and tuning enterprise

We are seeking a Staff Engineer to join our growing team to provide technical direction and implement core parts of a new platform we are building to make it easier for customers to build AI applications using MongoDB. As a Staff Engineer on this new team, you will be responsible for providing technical leadership to teams developing cutting edge technologies related to enabling deployment at scale of AI applications. You will take on challenging, high-visibility projects that improve and enhance the performance, scalability, and reliability of the distributed systems infrastructure for this new product. MongoDB engineering teams pride themselves on building high-quality software and living MongoDB cultural values every day. We value intellectual curiosity and honesty, and building together in an environment that prioritizes collaboration over competition. We're looking to speak with candidates based in the New York City area for our hybrid or in-office working models. Position Expectations Work closely with product management, product engineering, product design peers as well as other teams within the company to define the first version and future evolution of the service Design, build and deliver well-tested core pieces of the platform in collaboration with other vested parties Contribute to shaping architecture, code reviews and development practices, developer experience as the teams and product grow Mentor fellow engineers and assume ownership and accountability of projects Qualifications Strong background in building core components for high scale compute and data distributed systems 8+ years experience of building distributed systems, and/or foundational cloud services at scale and an interest in working with Python, Go and Java Proven success in designing, writing, testing, debugging, performance tuning, possessing a strong grip on the foundational materials of computer science and maintaining distributed and/or highly concurrent software s

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. Performance Engineer, Inference Engine About the Role Anthropic's inference engine is the software between the accelerator kernels and the routing layer. It manages the entire token path in between: batching requests, laying the model out across chips, managing memory for weights and activations, coordinating every forward pass, and managing model state across requests. Built in-house, it runs on all of our accelerator platforms, serving Claude to millions of users and running our research workloads. You will work on building and optimizing this system at Anthropic scale: improving throughput, cost, reliability, and latency across all accelerator and cloud platforms. You are intimately familiar with the hardware and bandwidth numbers (FLOPs, HBM, PCIe, RDMA, network links, etc.) and can model a problem quickly: where the time and bytes go, and what sets the bound. The role is deeply technical and high-impact, and suits engineers who enjoy working across accelerator programming, high-performance systems that seamlessly coordinate between host and device, and large-scale distributed systems. Familiarity with the transformer architecture is a plus. Some example recurring themes: Keep device utilization high. Accelerators should never be waiting due to other overheads. Reuse instead of recompute. Keep model state cached and reuse it whenever that is cheaper than computing it again. Measure, model, then change. We build the observability to see where the gaps are, model the impact of potential improvements, deploy them, and go around again, with Claude speeding up every turn of that loop. Tokens you can trust. Ensuring model quality matter

We're at a pivotal moment for both Tibber and the planet. When joining Tibber, you won’t just help scale a forward-thinking tech company – you’ll contribute to a real shift in how people consume electricity. With millions of smart devices connected to the Tibber platform (like electric vehicles and smart thermostats), we have one of the most unique portfolios trading energy on the market. We’re looking for a Principal Engineer to join us in making the energy transition happen – maybe that’s you? Job Mission 🚀 As our Principal Engineer , you'll report to our VP of Engineering and join our engineering org of ~80 people. You will serve as the technical authority driving the overarching architecture and engineering strategy across all of Tibber. You will bridge complex domain problems, from distributed real-time IoT pipelines to energy market integration, with resilient, high-scale software systems. Your work directly enables millions of smart devices to balance power grids across Europe, unlocking new horizons in sustainable energy consumption. What you'll do ✅ You will own the overall architecture and technical strategy for low-latency, highly resilient distributed systems capable of coordinating millions of connected smart devices in real time, working in close collaboration with senior staff and staff engineers to design and evolve these systems. You will set technical vision, standards, and best practices across domain teams, partnering with senior staff and staff engineers to drive engineering excellence and operational resilience. You will partner closely with product leaders and executive stakeholders to align long-term technical roadmaps with business objectives. You will evaluate emerging technologies, prototype novel concepts, and guide strategic tech-stack decisions to keep Tibber ahead of market shifts. You will mentor and empower senior engineering talent, elevating technical craft, architecture design capabilities, and problem-solving skills throughout t

We are seeking a Staff Engineer to join our growing Gurugram Products & Technology team to provide technical direction, direct architecture, and implement core parts of a new platform we are building to make it easier for customers to build AI applications using MongoDB. As a Staff Engineer on this new team, you will be responsible for providing technical leadership to teams developing cutting edge technologies related to enabling deployment at scale of AI applications. You will take on challenging, high-visibility projects that improve and enhance the performance, scalability, and reliability of the distributed systems infrastructure for this new product. MongoDB engineering teams pride themselves on building high-quality software and living MongoDB cultural values every day – we value intellectual curiosity and honesty, and building together in an environment that prioritizes collaboration over competition. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Position Expectations Work closely with research, product management, product engineering, product design, peers as well as other teams within the company to define the first version and future evolution of the service Design, build and deliver well-tested core pieces of the platform in collaboration with other vested parties Contribute to shaping architecture, code reviews and development practices, developer experience as the teams and product grow Mentor fellow engineers and assume ownership and accountability of projects Qualifications Strong background in building core components for high scale compute and data distributed systems 8+ years experience of building distributed systems, and/or foundational cloud services at scale and an interest in working with Python, Go and Java Proven success in designing, writing, testing, debugging, performance tuning, possessing a strong grip on the foundational materials of computer science and maint

We are seeking a Staff Engineer to join our growing Gurugram Products & Technology team to provide technical direction, direct architecture, and implement core parts of a new platform we are building to make it easier for customers to build AI applications using MongoDB. As a Staff Engineer on this new team, you will be responsible for providing technical leadership to teams developing cutting edge technologies related to enabling deployment at scale of AI applications. You will take on challenging, high-visibility projects that improve and enhance the performance, scalability, and reliability of the distributed systems infrastructure for this new product. MongoDB engineering teams pride themselves on building high-quality software and living MongoDB cultural values every day – we value intellectual curiosity and honesty, and building together in an environment that prioritizes collaboration over competition. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Position Expectations Work closely with research, product management, product engineering, product design, peers as well as other teams within the company to define the first version and future evolution of the service Design, build and deliver well-tested core pieces of the platform in collaboration with other vested parties Contribute to shaping architecture, code reviews and development practices, developer experience as the teams and product grow Mentor fellow engineers and assume ownership and accountability of projects Qualifications Strong background in building core components for high scale compute and data distributed systems 8+ years experience of building distributed systems, and/or foundational cloud services at scale and an interest in working with Python, Go and Java Proven success in designing, writing, testing, debugging, performance tuning, possessing a strong grip on the foundational materials of computer science and maint

About the Role We are seeking a platform engineer to join our Compute team. This team owns the critical systems that power project provisioning, scaling, and the compute that our users rely on every day. You’ll work on the core platform that ensures Supabase can seamlessly scale across multiple regions, handle high-volume workloads, and provide low-latency, highly available compute services. You'll design, build, and operate systems that are both robust and highly automated — enabling us to provision new projects reliably at scale, optimize resource utilization, and deliver a seamless experience to the millions of databases which we manage. What You’ll Be Responsible For: Help build and maintain the Supabase Cloud offering; Design and implement systems to provision, scale, and manage the multi-region compute workloads powering Supabase projects; Own the full lifecycle of compute orchestration: project creation, warm pools, autoscaling, resizing, and resource optimization; Improve automation and observability across the compute stack to ensure high availability and performance; Improve our system architecture to reduce costs while balancing security, reliability, and performance; Collaborate cross-functionally with other teams to help leverage compute as a core platform offering; Participate in on-call rotations, incident response, and post-incident reviews; Resolve escalated support issues, while also identifying and resolving systemic issues across the platform. You Might Be A Good Fit If You: Have strong software engineering skills (Go and Typescript required); Experience building and operating cloud infrastructure or distributed systems at scale; Have 5+ years experience with cloud infrastructure (AWS required, additional experience with GCP and Azure is a plus) - particularly compute, networking, and storage services; Have 3+ years experience working with building custom Kubernetes controllers, and operating large-scale (tens-to-hundreds of thousands of pods) cl

We are seeking a Senior Staff Engineer to join our growing Gurugram Products & Technology team to provide technical direction, direct architecture, and implement core parts of a new platform we are building to make it easier for customers to build AI applications using MongoDB. As a Senior Staff Engineer on this new team, you will be responsible for providing technical leadership to teams developing cutting edge technologies related to enabling deployment at scale of AI applications. You will take on challenging, high-visibility projects that improve and enhance the performance, scalability, and reliability of the distributed systems infrastructure for this new product. MongoDB engineering teams pride themselves on building high-quality software and living MongoDB cultural values every day – we value intellectual curiosity and honesty, and building together in an environment that prioritizes collaboration over competition. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Position Expectations Work closely with research, product management, product engineering, product design, peers as well as other teams within the company to define the first version and future evolution of the service Design, build and deliver well-tested core pieces of the platform in collaboration with other vested parties Contribute to shaping architecture, code reviews and development practices, developer experience as the teams and product grow Mentor fellow engineers and assume ownership and accountability of projects Qualifications Strong background in building core components for high scale compute and data distributed systems 15+ years experience of building distributed systems, and/or foundational cloud services at scale and an interest in working with Python, Go and Java Proven success in designing, writing, testing, debugging, performance tuning, possessing a strong grip on the foundational materials of computer sc

Senior: PLN 260,400 - 352,200 Subject to alignment to the responsibilities and duties of the role About the job Build quality foundations for Kubernetes systems that power next-generation AI compute. As a Senior QA Engineer , you will validate the workload management stack for new AI accelerator hardware. You will help ensure that Kubernetes integrations are reliable, scalable and ready for production use. Your work will support how accelerators are scheduled, orchestrated and used across distributed environments. You will test systems that make complex AI compute infrastructure dependable for real users. You will design and develop automated test suites, build system and integration tests, and contribute to improving CI/CD quality practices. You will also investigate and debug issues across Kubernetes, infrastructure and application layers. This role is for someone who enjoys hands-on technical testing, automation and working close to complex distributed systems. This is a hybrid position, with at least three days each week in our Gdańsk office. The team and culture You will join the Workload Management team, working closely with software engineers, infrastructure specialists and other QA engineers. The work is practical, systems-focused and based on strong technical ownership. Quality is built early here, not checked only at the end. You will contribute to test strategy, validation planning and automation practices throughout the development lifecycle. The team works through open technical discussion and evidence-based decisions. You will be encouraged to speak up on quality risks, improve test coverage and help turn complex systems into reliable products. As a senior member of the QA team, you will also support less experienced engineers through technical guidance, code reviews and sharing good testing practices. What we’re looking for Strong Python programming experience, with a focus on automation and test engineering Hands-on experience with Robot Framework or

As a Staff Engineer on Datadog's Compute – Disruption and Workload Placement team, you'll help define how our Kubernetes fleet scales to meet the demands of rapidly growing AI and cloud-native workloads. You'll work on the systems that ensure engineering teams have the right compute capacity, in the right region, at the right time across AWS, Google Cloud, and Azure. This is a highly technical, high-impact role where you'll shape the future of capacity orchestration, influence platform architecture, and solve infrastructure challenges that directly support Datadog's continued growth. 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'll Do: Lead the technical direction of capacity management and workload placement for Datadog's Kubernetes platform spanning 100,000+ virtual machines across multiple cloud providers. Design and build systems that optimize how engineering workloads are scheduled and deployed across regions while balancing capacity constraints, reliability, and performance. Partner across infrastructure teams to evolve multi-region and multi-cloud capacity orchestration as Datadog continues to scale. Develop production software in Go to improve Kubernetes platform capabilities, automation, and operational efficiency. Use data and capacity signals to influence infrastructure decisions, forecast growth, and improve workload placement strategies. Who You Are: You have significant experience designing and operating large-scale Kubernetes-based infrastructure or platform systems. You are an experienced software engineer with strong programming skills, ideally in Go or a comparable systems programming language. You have hands-on experience with at least one major cloud provider (AWS, Google Cloud, or Azure) and understand distributed cloud infrastructure. Yo

As a Staff Engineer on Datadog's Compute – Disruption and Workload Placement team, you'll help define how our Kubernetes fleet scales to meet the demands of rapidly growing AI and cloud-native workloads. You'll work on the systems that ensure engineering teams have the right compute capacity, in the right region, at the right time across AWS, Google Cloud, and Azure. This is a highly technical, high-impact role where you'll shape the future of capacity orchestration, influence platform architecture, and solve infrastructure challenges that directly support Datadog's continued growth. 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'll Do: Lead the technical direction of capacity management and workload placement for Datadog's Kubernetes platform spanning 100,000+ virtual machines across multiple cloud providers. Design and build systems that optimize how engineering workloads are scheduled and deployed across regions while balancing capacity constraints, reliability, and performance. Partner across infrastructure teams to evolve multi-region and multi-cloud capacity orchestration as Datadog continues to scale. Develop production software in Go to improve Kubernetes platform capabilities, automation, and operational efficiency. Use data and capacity signals to influence infrastructure decisions, forecast growth, and improve workload placement strategies. Who You Are: You have significant experience designing and operating large-scale Kubernetes-based infrastructure or platform systems. You are an experienced software engineer with strong programming skills, ideally in Go or a comparable systems programming language. You have hands-on experience with at least one major cloud provider (AWS, Google Cloud, or Azure) and understand distributed cloud infrastructure. Yo

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. Site Reliability Engineering at Affirm is a small, yet crucial, team that helps our Engineering partners to “Operate What They Own” with excellence to protect their customers’ experience. SRE accomplishes this through defining frameworks and best practices for operating applications, building tooling, and providing training and consulting. Some of the many SRE responsibilities are: Providing data and visibility to teams and leadership on application performance Guiding the development of SLOs Driving the Incident Management and Analysis process Steering the implementation of Change Management and Deployment practices Engaging in service and architectural conversations Recommending observability and alerting configurations The SRE team benefits from experience across many domains including: infrastructure, platform, and distributed systems capacity management, load and chaos testing automation, observability, and configuration management development and product experience The SRE team is seeking motivated software and systems engineers with the experience to build, iterate on, and expand incident lifecycle, reliability, and resilience practices throughout Affirms Engineering organization and beyond. What You'll Do: You will be responsible for owning and delivering quarterly goals for your team, leading engineers on your team through ambiguity to solve open-ended problems, and ensuring that everyone is supported throughout delivery. You will support your peers and stakeholders in the product development lifecycle by collaborating with infrastructure, product management, developer experience & analytics by participating in ideation, articulating technical constraints, and partnering on decisions that properly consider risks and trade-offs. You will proactively identify technical solutions

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. Site Reliability Engineering at Affirm is a small, yet crucial, team that helps our Engineering partners to “Operate What They Own” with excellence to protect their customers’ experience. SRE accomplishes this through defining frameworks and best practices for operating applications, building tooling, and providing training and consulting. Some of the many SRE responsibilities are: Providing data and visibility to teams and leadership on application performance Guiding the development of SLOs Driving the Incident Management and Analysis process Steering the implementation of Change Management and Deployment practices Engaging in service and architectural conversations Recommending observability and alerting configurations The SRE team benefits from experience across many domains including: infrastructure, platform, and distributed systems capacity management, load and chaos testing automation, observability, and configuration management development and product experience The SRE team is seeking motivated software and systems engineers with the experience to build, iterate on, and expand incident lifecycle, reliability, and resilience practices throughout Affirms Engineering organization and beyond. What You'll Do: You will be responsible for owning and delivering quarterly goals for your team, leading engineers on your team through ambiguity to solve open-ended problems, and ensuring that everyone is supported throughout delivery. You will support your peers and stakeholders in the product development lifecycle by collaborating with infrastructure, product management, developer experience & analytics by participating in ideation, articulating technical constraints, and partnering on decisions that properly consider risks and trade-offs. You will proactively identify technical solutions

Senior AI Engineer Location: London (Hybrid) | Practice Area : Technology & Engineering | Type: Permanent Empower the next frontier of AI with Capco. Shape, build, and deliver future-ready generative systems. The Role We’re looking for a Senior AI Engineer (Senior/Principal Consultant) to join our Technology Delivery team. In this role, you’ll combine deep expertise in AI/ML engineering and software development to design, build, and deploy advanced generative AI and agentic systems for leading financial services clients. You’ll work hands-on across the full AI engineering lifecycle, from architecting intelligent multi-agent systems to deploying scalable production-grade AI applications within enterprise environments. As a senior consultant, you’ll also collaborate closely with multidisciplinary teams and client stakeholders to drive innovation, accelerate adoption, and deliver measurable business impact. What You’ll Do Architect and develop autonomous AI systems leveraging multi-modal large language models across text, image, audio, and video Design and implement agentic workflows using prompt engineering, Retrieval-Augmented Generation (RAG), APIs, and enterprise data integrations Fine-tune, optimize, and deploy large language and multi-modal models with a focus on scalability, reliability, and low-latency performance Build scalable MLOps pipelines and cloud-native AI applications to support secure, production-grade deployments Collaborate with clients and cross-functional teams to shape AI engineering strategy and accelerate GenAI adoption across complex environments What We’re Looking For Bachelor’s degree or higher in Computer Science, Artificial Intelligence, Engineering, or a related STEM discipline Proven hands-on experience deploying LLMs and multi-modal AI models within enterprise or large-scale production environments Strong software engineering expertise in Python, including backend development, API design, and distributed systems Solid understan