Ai Infrastructure Systems Engineer 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 We are looking for a Finance & Strategy (FP&A) Systems Engineer to join our Finance Systems team at Anthropic. In this role, you will be responsible for building and maintaining platforms that support our core Financial Planning, Forecasting and Analytics processes. You will bring deep hands-on expertise in EPM platforms like Anaplan, Pigment and data platforms like BigQuery, who writes integrations, tooling, and production code that connect them to Anthropic’s ERP and data warehouse systems. You'll work closely with Corporate Finance & strategy stakeholders to translate business requirements into innovative technical solutions, maintain data integrity, and drive continuous improvements to our financial systems infrastructure. You'll manage day-to-day Finance system operations, support critical financial processes and monthly Forecasting cycles, and take on more ambitious system projects over time, including using Claude to automate FP&A work, help build scalable solutions that enable efficient financial planning, forecasting, and reporting as we continue to grow. Responsibilities Systems Administration and Support Serve as a primary system administrator for our financial planning platform (Pigment), maintaining system health and optimal performance Manage Finance applications, data, user access & security, system configurations, version management to ensure appropriate controls and governance. Provide technical support and troubleshooting for end-users, resolving issues and answering system-related questions System Development and Enhancement Design, build, and maintain application

About the Role We are seeking a Cloud Infrastructure Engineer to help design and evolve the platforms that power OpenAI’s products. In this role, you will be a hands-on technical leader, driving the architecture, scalability, reliability, and security of critical infrastructure systems. You will help define how we build and operate infrastructure at the next order of magnitude, while influencing technical direction across teams. This role is both deeply technical and highly strategic, requiring strong ownership, sound judgment, and the ability to partner effectively across engineering, product, and research organizations. In this role, you will: Design and build scalable, reliable, and secure infrastructure platforms that power OpenAI products Evolve cloud infrastructure abstractions that enable rapid product development across teams Architect systems to support significant growth, performance, and operational complexity Improve server orchestration, networking, distributed systems reliability, and infrastructure security posture Influence technical direction and infrastructure strategy across multiple teams Partner closely with product, research, and engineering teams to align infrastructure with evolving needs Own operational excellence, including participation in on-call rotations, incident response, and production readiness Mentor engineers and raise the overall technical bar of the organization Contribute to a culture of high ownership, low ego, and thoughtful collaboration You might thrive in this role if you: 8+ years of experience building and operating large-scale infrastructure systems Deep expertise in Kubernetes and container orchestration at scale Strong experience designing cloud abstractions and platform infrastructure (AWS, GCP, Azure, or similar) Proven track record of leading complex technical initiatives across teams Experience operating highly reliable, secure, and scalable distributed systems Security engineering experience or security backgroun

The team + the role Pendo's Applied AI team turns AI infrastructure into real business outcomes across Sales, Marketing, and Customer Engineering. AI here isn't a feature we bolt on — it's how we scale GTM capability across the company. We build AI that makes GTM teams measurably faster and more effective, and we measure success by whether those teams are actually using what we ship and getting real value from it. As an Applied AI Engineer, you'll own the full lifecycle of AI-powered solutions — from problem definition and prompt design through to production deployment and ongoing iteration. You'll work directly with GTM stakeholders to identify high-value problems, set realistic expectations about what AI can and can't do, and ship solutions that stick. The best person for this role has a strong engineering instinct, deep curiosity about how businesses operate, and the judgment to know when AI is the right tool — and when it isn't. This role is based in Raleigh, NC and follows Pendo's hybrid model: in-office 3 days per week. What this looks like day-to-day Own AI solutions end-to-end: problem definition, prompt design, production deployment, monitoring, and iteration — you ship, you watch, you improve. Build and manage GTM workflow automations that reduce manual work across Sales, Marketing, and Customer Engineering systems, including Slackbots and other integrations. Partner directly with GTM stakeholders to surface high-value problems, validate solutions, drive adoption, and set honest expectations about AI capabilities and limitations. Develop and maintain prompt management practices that make AI outputs reliable, auditable, and improvable over time — treat prompts as production code, not experiments. Work with the Data Platform and Systems teams to identify foundational tooling gaps and contribute clear, actionable requirements based on what you encounter in production. Share reusable AI workflow patterns and tool findings with the broader team — your impact sh

Who Are We? Postman is the world’s leading API platform, used by more than 45 million+ developers and 500,000 organizations, including 98% of the Fortune 500. Postman is helping developers and professionals across the globe build the API-first world by simplifying each step of the API lifecycle and streamlining collaboration—enabling users to create better APIs, faster. The company is headquartered in San Francisco and has offices in Boston, New York, Austin, Tokyo, London, and Bangalore - where Postman was founded. Postman is privately held, with funding from Battery Ventures, BOND, Coatue, CRV, Insight Partners, and Nexus Venture Partners. Learn more at postman.com or connect with Postman on X via @getpostman. P.S: We highly recommend reading The "API-First World" graphic novel to understand the bigger picture and our vision at Postman. The Opportunity Postman is seeking an experienced AI Systems Reliability Engineer to help define, build, and maintain the infrastructure and processes that ensure the reliability, scalability, and performance of Postman’s AI-powered API and agentic systems in production. This role focuses on monitoring, availability, incident response, and automation to support AI services and tools trusted by millions of developers globally. What You’ll Do Develop and manage reliability metrics (SLOs) for AI-driven API services and agentic AI platform features Implement comprehensive observability and monitoring systems for real-time performance and fault detection Design and drive automated failover, recovery, and incident response strategies for high-availability AI infrastructure Optimize resource utilization, particularly GPU/accelerator efficiency, ensuring cost-effective AI system operation Collaborate closely with engineering, platform, and product teams to align reliability efforts with broader organizational goals Lead efforts to build internal tooling and automation focused on AI system stability and operational excellence Drive continuo

About the Role The AI Acceleration team’s mission is to make Perplexity the best place to build and ship software with AI agents. We build the infrastructure that engineers and agents rely on, and develop new ways for agents to write, test, review, and ship code. Our work helps teams move from an idea to production faster, without compromising quality or reliability. We own the end-to-end development experience at Perplexity, from the environment where code is written to the systems that ship it to production. That includes local and cloud coding environments, build and test infrastructure, code review, and release management. We’re also building autonomous software development systems, where agents take on increasingly complex engineering work with explicit evaluation, verification, and safety controls. We own both the infrastructure these systems depend on and the workflows that make them useful. As an AI Acceleration Engineer, you’ll turn emerging agent capabilities into dependable systems used across Perplexity. You’ll work directly with engineers to understand where development slows down, experiment with new approaches, and take promising ideas through to production. This role combines systems engineering, developer experience, and hands-on agent development, with a direct measure of success: helping teams spend less time on delivery overhead and more time building products. Responsibilities Identify, prioritize, and deliver the highest-impact opportunities to accelerate how Perplexity builds and ships software with AI. Work directly with engineering and business teams to understand their workflows, constraints, and bottlenecks, and build solutions that address how they actually work. Build and operate the infrastructure that engineers and agents depend on, including development environments, build and test systems, code review, and release tooling. Make our codebases, systems, and internal knowledge easier for agents to navigate, understand, and use through b

About the job Build the cloud platform that puts Graphcore AI systems into real use. As a Senior Cloud Engineer, you will develop and operate private cloud services for Graphcore teams and users. You will turn product and user requirements into reliable, deployed services. Your work will support large-scale AI systems built from Graphcore hardware, high-performance servers, networks and storage. These systems help engineers validate, benchmark and optimise the platforms behind advanced AI compute. You will use Infrastructure-as-Code, observability and automation to deploy, test and improve cloud infrastructure. You will also work with datacentre, software and product teams to keep critical systems performing. This is hands-on engineering with real ownership. You will often work with pre-release hardware and software, where judgement and pace matter. The team and culture The Cloud Platform Team builds the systems that give internal users and customers access to Graphcore AI infrastructure. Work moves from requirements to deployed services, with engineers close to the users and systems they support. You will work across Software Platform, Datacentre Operations and Product Development. Decisions are shaped by technical evidence, user needs and the realities of operating critical infrastructure. This team suits engineers who take responsibility, speak up and move quickly. You will be trusted to work independently, solve hard platform problems and keep services available. What we’re looking for Bachelor's degree or equivalent practical experience in a relevant subject. Solid software engineering or IT experience, with proven delivery as an individual contributor. Experience managing on-premises or private-cloud environments. Strong Linux scripting and system administration skills across bash, Python, awk, sed, Ubuntu, RHEL and variants. Experience with Git, CI pipelines and Infrastructure-as-Code tools such as Terraform/OpenTofu, Ansible or Packer. Hands-on

About the job Own the reliability of AI compute hardware where lab discovery becomes data centre reality. Graphcore is building the hardware and systems infrastructure needed for the next generation of AI breakthroughs. This role helps prove those platforms work when complexity, scale and pressure increase. You will lead advanced operational, diagnostic and engineering support across lab and data centre environments. Your work will improve hardware bring-up, validation and troubleshooting for AI compute platforms. You will diagnose failures across server blades, racks, power systems, thermal behaviour, network configuration and BIOS/BMC issues. You will turn hard problems into clear root cause analysis, corrective action and better operating practice. This is hands-on engineering with visible impact. You will support new platforms from early bring-up through deployment, helping Graphcore move faster with confidence. The team and culture You will work with Systems Engineering, Hardware Engineering, server engineering, firmware, platform architects and data centre operations. Problems are solved close to the hardware, with clear evidence and direct ownership. The team moves quickly during bring-up and validation cycles. Engineers are expected to act fast, take responsibility and speak up when something needs attention. Decisions are shaped by data, system behaviour and practical engineering judgement. You will guide others, improve documentation and help raise the standard of hardware diagnostics. What we're looking for · Strong knowledge of server hardware architectures and board-level debugging · Experience isolating failures using system logs, telemetry, power data and thermal metrics · Hands-on experience with HPC systems, AI compute platforms or rack-scale infrastructure · Ability to lead structured root cause analysis and propose practical corrective actions · Confidence working across engineering, platform and data centre teams · Clear written and verbal

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role You will define and build the CI/CD systems that qualify frontier models and the software stack running on OpenAI’s custom AI accelerators. Your work will make correctness, performance, and stability measurable on every change, from individual commits through production releases. This role spans model workloads, accelerator software, systems infrastructure, and developer productivity. You will establish scalable CI/CD, GitOps, and monorepo practices; design trustworthy regression and benchmarking pipelines; and partner with model, compiler, kernel, runtime, firmware, and hardware teams to shorten feedback loops without compromising production readiness. In this role, you will: Define the model CI strategy for frontier models running on OpenAI custom silicon and integrated accelerator systems. Build production CI/CD pipelines for functional regression, performance benchmarking, software stability, and release qualification. Design representative test matrices across models, configurations, hardware generations, software components, and deployment environments. Create reliable performance baselines, regression detection, bisect and triage workflows, and clear ownership for failures. Establish GitOps practices for reproducible configuration, promotion, rollback, auditability, and environment consistency. Shape monorepo architecture, dependency management, build and test boundaries, change validation, and developer workflows at scale. Develop scalable orchestration

P-1563 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started in Bengaluru , India ! As a software engineer with a backend focus, you will work with your team to build infrastructure for the Databricks platform at scale. About the Team We manage the infrastructure efficiency for one of the world's largest data and AI platforms. Operating at massive scale across AWS, Azure, and GCP, our mission is to ensure that every dollar spent on cloud infrastructure is optimized. The MCE team builds the critical tools, frameworks, and automated systems that provide deep cost visibility and ensure maximum resource utilization. We aren't just cutting costs; we are engineering systems to scale efficiently as our cloud footprint expands into the hundreds of millions of dollars. The Role As a Staff Software Engineer, you will serve as the technical lead for the Bengaluru MCE chapter. You will be responsible for defining the technical strategy for efficiency projects where the solutions are not yet known. You will lead cross-functional efforts, working with finance and cost team, to tackle massive-scale engineering challenges, ensuring our systems can automatically drive cost efficiency and handle the complexity of global, multi-cloud data processing without compromising on performance or stability. As one of the founding senior engineers of the Bengaluru MCE chapter — a team that has already deliver

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software, and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers, and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary Reporting to the Validation leadership team, the Principal Execution and Quality Validation Engineer will be responsible for driving validation execution, automation, product quality, and release readiness across Graphcore silicon and platform technologies. The role combines deep expertise in hardware validation, test automation, and quality engineering with a strong focus on execution excellence. Working closely with architecture, design, verification, firmware, software, systems engineering, and validation teams, the successful candidate will develop scalable validation methodologies, improve test coverage and execution efficiency, and ensure products meet the highest standards of functionality, reliability, and performance before customer deployment. As a recognized technical leader within the validation organisation, this role will influence validation strategies, automation roadmaps, and quality practices across multiple projects and engineering disciplines. The Team The Validation Execution and Quality team sits within the Validation organisation and is responsible for improving validation effectiveness, te

About the Team OpenAI’s Compute organization turns ambitious AI research into real-world capability by delivering the compute infrastructure behind our most advanced models. The team works across software, hardware, facilities, operations, and engineering disciplines to make enormous amounts of compute available, reliable, and efficient. As the demand for frontier AI grows, so does the complexity of the systems required to support it. Scaling this infrastructure means solving problems that cut across distributed systems, ML infrastructure, GPU fleets, power, cooling, networking, manufacturing, supply chain, and data center delivery. Our work is focused on expanding the compute foundation that enables OpenAI to train more capable models, including systems like GPT-5.6, and make frontier AI available to more people, products, and workflows. We’re looking for exceptional people across many disciplines to help build the next generation of AI infrastructure at a scale few organizations have attempted. About the Role We are hiring across a broad range of roles to help design, build, scale, and operate OpenAI’s compute infrastructure. Depending on your background, you may work on large-scale distributed systems, ML infrastructure, hardware systems, manufacturing, supply chain, data center development, or the physical engineering systems required to bring massive compute capacity online. You’ll work with teams across research, engineering, hardware, operations, and infrastructure to solve high-impact problems at extraordinary scale. This may include improving system reliability, accelerating deployment timelines, increasing operational efficiency, designing new infrastructure, or helping bring new compute platforms and facilities from concept to production. This is an opportunity to work on one of the most important infrastructure challenges in AI: building the compute foundation required to train and serve increasingly capable frontier models. Key Responsibilities Help bui

P-1563 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started in Bengaluru , India ! As a software engineer with a backend focus, you will work with your team to build infrastructure for the Databricks platform at scale. About the Team We manage the infrastructure efficiency for one of the world's largest data and AI platforms. Operating at massive scale across AWS, Azure, and GCP, our mission is to ensure that every dollar spent on cloud infrastructure is optimized. The MCE team builds the critical tools, frameworks, and automated systems that provide deep cost visibility and ensure maximum resource utilization. We are looking for engineers to help us engineer systems that optimize our footprint as we scale into the hundreds of millions of dollars in cloud spend. The Role As a Senior Software Engineer, you will own the end-to-end design and delivery of high-impact engineering projects. You will act as a primary owner of key system components, handling technical ambiguity, collaborating with stakeholders, and delivering robust, scalable solutions. Your work will directly impact our infrastructure margins by building the next generation of cost attribution, automated resource management, and efficiency tooling. The impact you will have End-to-End System Design : Lead projects from concept to deployment. You will design and build scalable systems that handle high-volume data streams

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software, and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers, and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary Reporting to the Validation leadership team, the Senior Execution and Quality Validation Engineer will be responsible for executing validation plans, developing automation solutions, and improving product quality across Graphcore silicon and platform technologies. Working closely with architecture, design, verification, firmware, software, systems engineering, and validation teams, the successful candidate will contribute to scalable validation methodologies, improve test coverage and execution efficiency, and help ensure products meet high standards of functionality, reliability, and performance before customer deployment. The role requires strong technical skills, attention to detail, and a passion for improving validation quality through effective execution, automation, and continuous improvement. The Team The Validation Execution and Quality team sits within the Validation organisation and is responsible for improving validation effectiveness, test execution efficiency, product quality, and release readiness across Graphcore silicon and platform products. The team develops validation methodologies, automation

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Job Summary We build the automation, infrastructure, and validation systems that bring new computing platforms to life at scale! Our team lives at the intersection of hardware and software, turning tough engineering challenges into reliable, repeatable workflows. When a new platform needs to be provisioned, orchestrated, and qualified, we're the ones who make it happen—and we genuinely enjoy the work. As our Staff Platform Integration Engineer, you'll be the driving force behind getting emerging platforms ready for scaled testing and qualification. This is a software-focused role: you'll blend hands-on development, infrastructure engineering, and technical leadership to build the systems our engineers depend on every day. You'll work with firmware integration points and build a working understanding of incoming hardware capabilities—while our dedicated hardware team owns the physical handling and debug. If you like solving problems that span software, automation, and firmware integration, this is a role where your work directly advances our most meaningful achievements. Responsibilities : Integrate new computing platforms into automation, provisioning, observability, and test orchestration ecosystems through software and firmware integration points Design and maintain full-stack applications, APIs, automation services, and operational tooling Build infrastructure automation, deployment pipe

About Graphcore Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. The Role: We are developing the next generation of AI compute, a large-scale system-on-chip (SoC) designed to power future high-performance AI systems. As the SoC Validation Lead, you will be responsible for enabling pre-production software to run reliably on new silicon quickly and efficiently, before showing that the silicon meets the highest standards of quality, reliability and functionality, ready for production deployment. You will lead a team delivering post-silicon validation across the full AI SoC, working across silicon, firmware, and platform levels. The role requires a deep technical understanding, strong hands-on debug experience, and the ability to collaborate effectively with hardware, software, and systems engineering teams. Responsibilities: Define and lead post-silicon validation strategy Develop and refine the overall post-silicon validation approach for our AI SoCs, ensuring reliable and timely delivery of validated silicon, architectural correctness, feature robustness, and at-scale system reliability. Drive cross-domain debug and issue resol