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Ai Infrastructure Systems Engineer Jobs

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Explore current ai infrastructure systems engineer jobs. Use filters to narrow by work mode, employment type, experience and date posted.

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Perplexity
📍 San Francisco• Full-time• $220K – $405K/yr
1mo ago

Perplexity API Platform Perplexity innovates at the frontier of AI infrastructure, search, and orchestration to serve the world's most discerning users. The Perplexity API Platform brings our technology to the world's most discerning developers. From exabyte-scale knowledge indexes to codegen-first agent runtimes, the building blocks behind Perplexity's applications are some of the most battle-tested AI systems in the industry. We believe these same building blocks can and should power the aspirations of builders everywhere. It's one thing to solve planet-scale retrieval, long-horizon orchestration, and other foundational AI challenges within a single product ecosystem. The true measure of success is to turn those solutions into elegant APIs that delight developers and agents alike. Our API Platform delivers frontier intelligence to thousands of customers: startups, trillion-dollar enterprises, U.S. and allied governments, and everyone in between. We've achieved incredible scale, yet we're just getting started. Join us to build tools for curious minds. About this role Perplexity is seeking strong engineers with a passion for delivering frontier intelligence and infrastructure to developers. Our company builds technology that reshapes how people search, reason, and interact with the world around them. Week after week, we observe increasing demand for programmatic interfaces to that technology. The API Platform engineering team is charged with designing, implementing, and scaling these interfaces. As a member of our team, you'll work on an eclectic portfolio spanning distributed systems, performance optimization, agent orchestration, and frontier topics that often change with each passing month. Throughout this work, you'll prioritize great developer and agent experience alike. You'll also define technical strategy for how we scale to meet compounding growth exponentials (number of customers, agents per customer, compute/retrieval per agent, etc.). Key Responsibilitie

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Affirm
📍 Poland• Full-time• Remote• $384K – $576K/yr
2mo ago

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

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Affirm
📍 Spain• Full-time• Remote• €86K – €122K/yr
2mo ago

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

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Anthropic
📍 Ca New York City• $320K – $485K/yr
3mo ago

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 Anthropic manages one of the industry's largest AI fleets — spanning multiple accelerator families, cpu families and clouds. The Capacity Engineering team is responsible for making sure all our infrastructure resources are accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute. As an engineer on Capacity Engineering, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on. You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around Capacity. You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams. The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment. This is a pipeline role feeding four areas. Depending on your background and business priority, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap: Data platform Pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, normalize billing and usage across cloud providers, and serve the BigQuery

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Cloudflare
📍 Hybrid• Full-time• Hybrid• $170K – $275K/yr
7mo ago

About Us At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in. Available Locations Austin, US New York, US San Francisco, US Responsibilities Lead and Mentor: Manage a high-performing team of kernel and systems engineers, fostering a culture of "collaboration-first" and continuous knowledge sharing both internally and with the global open-source community. Own the OS Lifecycle: Oversee the end-to-end delivery of the Linux Kernel and core OS components. Your goal is a fully automated continuous delivery pipeli

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Stripe
📍 Chicago• Full-time• Remote
28mo ago

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team Stripe Infrastructure is responsible for the reliability, scale, performance, and cost of Stripe's systems and the productivity and sentiment of Stripe's people. You may work on a wide variety of critical business areas including: Core Infrastructure—We're the home for Stripe's critical tier0 infrastructure systems (Compute, Networking, DocumentDB, Distributed Caching and High assurance engineering). We build the foundational platform for Stripe products and services to allow them to operate at scale. We drive reliability, availability, efficiency, and scalability of these systems. Developer Infrastructure—We're responsible for the productivity of all developers at Stripe. Ensure Stripe's engineers have a reliable, fast, and easy-to-use inner dev loop to maximize productivity while building everything from low-latency microservices to large-scale data pipelines and machine learning models. Data Infrastructure—We're responsible for offering data serving infrastructure spanning across data warehouse analytics, streaming analytics, and search capabilities. The stack is supported by a collection of internally developed large-scale distributed services and several popular open-source technologies like Trino/Presto, Apache Pinot, Hive Metastore, ElasticSearch etc. The systems we own support all of the data serving needs of high-scale services and thousands of individual Stripes across the company. Admin Platform—We empower Stripes to quickly

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A
Anthropic
📍 Seattle• $320K – $485K/yr
3 days ago

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 Anthropic manages one of the largest and fastest-growing infrastructure fleets in the industry — spanning multiple accelerator families, cpu families and clouds. The Capacity Engineering team is responsible for making sure all our infrastructure resources are accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute. As an engineer on Capacity Engineering, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on. You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around one of Anthropic’s largest areas of spend. You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams. The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment. This is a pipeline role feeding four areas. Depending on your background and business priority, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap: Data platform Pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, norma

pythonsqlazure
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A
Anthropic
📍 New York• $320K – $485K/yr
3 days ago

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 Anthropic manages one of the largest and fastest-growing infrastructure fleets in the industry — spanning multiple accelerator families, cpu families and clouds. The Capacity Engineering team is responsible for making sure all our infrastructure resources are accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute. As an engineer on Capacity Engineering, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on. You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around one of Anthropic’s largest areas of spend. You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams. The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment. This is a pipeline role feeding four areas. Depending on your background and business priority, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap: Data platform Pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, norma

pythonsqlazure
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A
Anthropic
📍 San Francisco• $320K – $485K/yr
3 days ago

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 Anthropic manages one of the largest and fastest-growing infrastructure fleets in the industry — spanning multiple accelerator families, cpu families and clouds. The Capacity Engineering team is responsible for making sure all our infrastructure resources are accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute. As an engineer on Capacity Engineering, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on. You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around one of Anthropic’s largest areas of spend. You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams. The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment. This is a pipeline role feeding four areas. Depending on your background and business priority, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap: Data platform Pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, norma

pythonsqlazure
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Lyft
📍 Toronto• Full-time• From C$108K/yr
2mo ago

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Our Infrastructure team is passionate about building software to solve problems at massive scale. We do this often, and when we believe our solution is worth sharing with the community, such as Envoy Proxy , we open source our ideas for the benefit of others. As an Observability team member, you are responsible for the operation and maintenance of our logging and metrics infrastructure. You ensure all teams at Lyft are aware of the operational health of their products by monitoring system availability and take a holistic view of our platform performance. You build software and platforms to automate infrastructure platform operations and management. By measuring and monitoring our operations you find opportunities to improve our systems in order to push our platform forward. You provide our partners with the support they need to help them build robust large scale distributed systems. We count on the reliability of our infrastructure to empower Lyft teams to provide our customers rich experiences that are highly available with rock solid performance to ensure our transportation platform continues to connect people and places. As we grow our team, we are seeking experienced Infrastructure Engineer to ensure that as our Infrastructure continues to scale, our platform continues to provide an essential and dependable service that transports millions of people every day. Specifically we are searching for someone who brings fresh perspectives, enjoys collaborating with cross-functional teams in order to continually improve our products and services for our customers. Responsibilities: Maintain, improve, and develop tooling and systems that enhance the reliability, scalability, and efficiency of our platform. Assist engineering teams in defining service-level objectives (SLOs) and provide the necessary toolin

pythonawskubernetes
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Affirm
📍 Canada• Remote• C$153K – C$213K/yr
2mo ago

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. Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest. We’re looking for a Software Engineer to design and build a next-generation reliability platform for Affirm’s production systems. You’ll blend traditional distributed systems engineering with AI-assisted development to give teams a single place to understand, debug, and improve the health of their services. This is a highly creative, hands-on role for someone who loves “vibe coding” — rapidly iterating, shipping, and refining with strong intuition— while still holding a very high bar for reliability, quality, and maintainability. 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 product management, design & analytics by participating in ideation, articulating technical constraints, and partnering on decisions that properly consider risks and trade-offs. · You will proactively identify project, process, technology or business issues, advocate for them, and lead in solving them. · You will support the operations and availability of your team’s artifacts by creating and monitoring metrics, escalating when needed, and supporting “keep the lights on” & on-call efforts. · You will foster a culture of quality and ownership on your team by setting or improving code review and design standards for your team, and advocating for them beyond your team through your writing and tech talks. · You will help develop talent on your team by pr

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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. Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest. We’re looking for a Software Engineer to design and build a next-generation reliability platform for Affirm’s production systems. You’ll blend traditional distributed systems engineering with AI-assisted development to give teams a single place to understand, debug, and improve the health of their services. This is a highly creative, hands-on role for someone who loves “vibe coding” — rapidly iterating, shipping, and refining with strong intuition— while still holding a very high bar for reliability, quality, and maintainability. 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 product management, design & analytics by participating in ideation, articulating technical constraints, and partnering on decisions that properly consider risks and trade-offs. · You will proactively identify project, process, technology or business issues, advocate for them, and lead in solving them. · You will support the operations and availability of your team’s artifacts by creating and monitoring metrics, escalating when needed, and supporting “keep the lights on” & on-call efforts. · You will foster a culture of quality and ownership on your team by setting or improving code review and design standards for your team, and advocating for them beyond your team through your writing and tech talks. · You will help develop talent on your team by pr

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Affirm
📍 Canada• Remote• C$181K – C$241K/yr
2mo ago

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. Engineering owns cost visibility and optimization across Affirm's cloud and AI infrastructure. We're the team that tells the business what it's spending, why it's changing, and what to do about it — from AWS resource waste and tagging strategy to the newer frontier of AI/LLM spend across the company's growing set of AI tools. We treat cost anomalies with the same rigor as production incidents: we've built a severity framework (mirroring Affirm's SEV0–3 incident model but mapped to dollar impact) with defined detection sources, TTD/TTR metrics, and escalation paths, and we operate a clear RACI with partner orgs — we own visibility and alerting, and partner teams own remediation (at times we may dig in deep and own remediation too!), so accountability never gets diffuse. As a Staff Cost Engineer, you'll operate at the intersection of finance, infrastructure, and data engineering — designing the tooling, automation, and processes that scale cost governance across a fast-growing multi-cloud and multi-AI-vendor footprint. You'll set technical direction for the team, influence cost strategy with infra and platform leaders across the org, and turn ambiguous "why did spend spike" questions into durable systems and self-service tooling. We're a small, high-leverage team — you'll have outsized influence on how Affirm thinks about cost. What You'll Do · You will be responsible for setting technical strategy for your team on a year-long time scale, and help your team tie it together with critical, business-impacting projects. · You will collaborate across teams in the product development lifecycle by collaborating with product management, design & analytics to ensure technical sustainability, risks and trade-offs are well understood and managed. · You will act as a force-multiplier for your team th

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Lyft
📍 Toronto• Full-time• From C$108K/yr
2mo ago

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. We are building and maintaining a highly scalable asynchronous platform that empowers our organization to handle critical business cases. As a software engineering team, our mission is to create robust and innovative solutions that drive the success of our business and deliver unparalleled value to our customers. We adopt Infrastructure as Code practice to automate the provisioning and configuration of our resources, which helps reduce manual configuration and improve consistency. Our team culture is built on collaboration, open communication, and a supportive environment where each member's ideas are valued and contributions are recognized. We believe in the importance of fostering a positive workplace culture that inspires innovation and creativity. Responsibilities: Maintain and analyze metrics from; operating systems; control planes; and applications to assist in fault detection and performance enhancement Design, develop and deploy tooling and systems that continually improve the reliability, scalability and efficiency of our platform Balance feature development speed and reliability with service-level objectives Operate and improve our Infrastructure using industry best practices and tools Participate in design and production readiness reviews, platform management and capacity planning ceremonies with cross-functional teams Document Infrastructure operations process and insights, identify repeatable actions and ruthlessly automate repetitive tasks Participate in our teams on-call rotations, respond to incidents and support other teams mitigate customer impacting events Experience: 5+ years experience working on teams responsible for software development, automation and systems engineering Experience building large-scale infrastructure, distributed systems or networks. Knowledge with SQS,

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18mo ago

Note: if you are an intern, new grad, or staff applicant, please do not apply using this link and visit our jobs page for those specific postings. Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the Organization Secure Frameworks: We provide security guarantees for common threats, helping teams secure their services by default. We build and maintain core application-layer security libraries and frameworks for development teams, including web security frameworks, cryptography libraries, and other threat mitigations across the Stripe technology stack. More recently, our scope has expanded to protective measures for AI agents. We are a hands-on engineering team that builds security protections and frameworks, rather than conducting security reviews. Core Infrastructure : We’re the home for Stripe's critical tier0 infrastructure systems (Compute, Networking, DocumentDB, Distributed Caching and High assurance engineering). We build the foundational platform for Stripe products and services to allow them to operate at scale. We drive reliability, availability, efficiency and scalability of these systems. Developer Infrastructure : We’re responsible for the productivity of all developers at Stripe. Ensure Stripe’s engineers have a reliable, fast, and easy-to-use inner dev loop to maximize productivity while building everything from low-latency microservices to large-scale data pipelines and machine learning models. Reliability Insights and Excellence : We build tools and frameworks

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