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System Engineer Jobs

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

O
1mo ago

About the Team Business Systems / Enterprise Platform Technology builds the internal systems, data foundations, workflow infrastructure, and enterprise platforms that help OpenAI operate at scale. The EPT AI Pod builds AI-native internal apps, MCP connectors, multi-agent workflows, and reusable platform capabilities across Finance, People, and GTM. About the Role As an Enterprise Applied AI Engineer, you will build internal apps for enterprise operations and the shared platform components those apps run on. This includes MCP connectors, multi-agent orchestration, data architecture, evals, monitoring, auditability, and governance. We’re looking for a hands-on engineer who is strong in Python, system design, enterprise integrations, data architecture, and applied AI systems. You should be excited to turn ambiguous business workflows into reliable internal products and shared infrastructure. In this role, you will: • Build internal apps for enterprise operations across Finance, People, and GTM • Build MCP connectors and enterprise integrations with strong auth, permissions, idempotency, retries, and rate-limit handling • Design end-to-end multi-agent workflows with tool routing, human approvals, audit trails, and safe action boundaries • Design data architecture for operational AI systems, including ingestion, schemas, quality checks, lineage, and governance • Build evals, monitoring, metrics, and regression tests for agentic workflows • Create reusable infrastructure, patterns, and components that other enterprise teams can build on • Partner with system owners and business owners to turn messy enterprise workflows into reliable internal products You might thrive in this role if you: • Have strong Python engineering skills for backend services, MCP connectors, agent/tool workflows, eval harnesses, and data ingestion jobs • Have strong system design skills across shared infrastructure, app architecture, reliability, and scaling • Have experience building internal apps,

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O
OpenAI
📍 San Francisco• Full-time
1mo ago

This role will support the fleet infrastructure team at OpenAI. The fleet team focuses on running the world’s largest, most reliable, and frictionless GPU fleet to support OpenAI’s general purpose model training and deployment. Work on this team ranges from Maximizing GPUs doing useful work by building user-friendly scheduling and quota systems Running a reliable and low maintenance platform by building push-button automation for kubernetes cluster provisioning and upgrades Supporting research workflows with service frameworks and deployment systems Ensuring fast model startup times though high performance snapshot delivery across blob storage down to hardware caching Much more! About the Role As an engineer within Fleet infrastructure, you will design, write, deploy, and operate infrastructure systems for model deployment and training on one of the world’s largest GPU fleet. The scale is immense, the timelines are tight, and the organization is moving fast; this is an opportunity to shape a critical system in support of OpenAI's mission to advance AI capabilities responsibly. This role is based in San Francisco, CA. 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: Design, implement and operate components of our compute fleet including job scheduling, cluster management, snapshot delivery, and CI/CD systems. Interface with researchers and product teams to understand workload requirements Collaborate with hardware, infrastructure, and business teams to provide a high utilization and high reliability service You might thrive in this role if you: Have experience with hyperscale compute systems Possess strong programming skills Have experience working in public clouds (especially Azure) Have experience working in Kubernetes Execution focused mentality paired with a rigorous focus on user requirements As a bonus, have an understanding of AI/ML workloads About OpenAI OpenAI is an AI resea

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O
1mo ago

About the Team Frontier Systems Foundations, part of Compute Foundations at OpenAI, builds the systems software foundation that turns new compute infrastructure into reliable, usable capacity for frontier model training. Our mission is to make some of the world's largest GPU clusters work reliably for frontier training. We bring new platforms and clusters online, safely maintain installed fleets, and partner with hardware, infrastructure, and research teams to resolve the system-level issues that keep jobs from running. That means building and maintaining the software closest to the machine: Linux and Ubuntu operating-system images, kernels and modules, drivers, packages and repositories, disks and boot configuration, firmware integration, provisioning, and system-level validation. We make these components reproducible, compatible, and safe to operate across heterogeneous fleets. About the Role We are looking for systems software engineers with deep Linux and host-systems experience to build, qualify, and maintain the operating-system foundation for OpenAI's frontier compute fleet. Relevant backgrounds include kernel and module development, Linux distribution or image engineering, package management, firmware and driver integration, disks and boot, and bare-metal provisioning. You'll work closely with hardware engineers, vendors, and infrastructure teams to bring up new platforms, integrate system components, and debug failures across firmware, disks, boot, operating systems, kernels, drivers, and workload interactions. Your work will directly influence how quickly new capacity becomes usable and how reliably large GPU fleets operate. You should be comfortable writing and maintaining production-quality systems software and automation, but we do not expect expertise across every layer. This is an opportunity to go deep on challenging systems problems while building the image, package, qualification, and recovery paths that power the next generation of frontier models

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O
1mo ago

About the Team Our London-based team builds the backend systems that help ChatGPT scale reliably. We work on infrastructure close to the product, partnering with engineering teams to improve the performance, resilience, and operability of critical user-facing systems. Our work combines backend software engineering with distributed systems and production reliability. We build shared capabilities, improve high-traffic workflows, and make it easier to introduce new product functionality without compromising performance or availability. About the Role This role is for software engineers who want to build and evolve backend systems operating at significant scale. You’ll write production code, design shared infrastructure, and solve technical challenges involving performance, distributed systems, and system reliability. You’ll also own how those systems behave in production: how changes are rolled out, how issues are detected and diagnosed, and how recurring operational problems can be addressed through better software and system design. This is a strong fit for backend engineers who enjoy complex systems problems and want a direct connection between the infrastructure they build and the experience of ChatGPT users. In this role, you will: Design, build, and maintain backend systems supporting high-traffic ChatGPT experiences. Develop shared services, APIs, and infrastructure that help product teams build and launch new capabilities safely. Improve the performance, scalability, and efficiency of production systems as usage and product complexity grow. Build and improve systems for asynchronous processing and other large-scale backend workloads. Lead architectural improvements and infrastructure migrations while maintaining correctness, compatibility, and safe rollout and rollback. Strengthen monitoring, alerting, and diagnostics to detect problems early and reduce customer impact. Participate in on-call, incident response, and root-cause analysis, and turn operational lea

awsrestai
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O
OpenAI
📍 San Francisco• Full-time
1mo ago

About the Team Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role We are seeking a Mechanical Engineer to design and prototype novel tactile, proprioceptive and force sensor solutions. You will work closely with experienced engineers and cross-functional partners to set functional requirements, develop and iterate on hardware to meet program expectations. This role is aimed at candidates with strong fundamentals in mechanical system design and robotic sensing including tactile sensors, force sensing and position sensing. You will contribute to real hardware programs moving from prototype through early production. You will lead both new sensor subsystem development and ongoing improvements to existing systems based on testing, field performance, and manufacturing feedback. This role is based in San Francisco, CA, and requires in-person presence 4 days a week. In this role, you will Lead the design and iteration of mechanical subsystems, including tactile sensors, load cells, force torque sensors and joint encoders. Create and maintain CAD models, assemblies, and drawings with appropriate tolerancing and documentation. Build and test prototypes, supporting debugging of mechanical issues such as fit, alignment, friction, and wear. Assist in developing test methods and executing validation to evaluate performance, durability, calibration and failure modes. Work with cross-functional teams to integrate mechanical components with sensors, actuators, and control systems. Support transition of designs from prototype to manufacturable assemblies, incorporating DFM and DFA considerations. Collaborate with manufact

awsrestai
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O
OpenAI
📍 San Francisco• Full-time
1mo ago

About the Team: OpenAI's mission is to ensure that artificial general intelligence (AGI) benefits all of humanity. Our API is the industry's most widely adopted AI platform, empowering startups, indie developers, and Fortune 500 companies alike. Through multimodal APIs—spanning real-time interactions, text-to-speech (TTS), speech generation, and image generation—we enable users to harness the full potential of diverse AI modalities effectively and at scale. About the Role: We are seeking an Engineering Manager to lead our multimodal API product suite. Your team will be responsible for delivering innovative APIs across real-time processing, speech transcription, speech generation, and image creation. You will own the product roadmap for how we evolve our multimodal API offerings, and you will build the products that allow developers to reach millions of end users through AI audio, video, and images. In this role, you will: Build, mentor, and grow a high-performing engineering team focused on multimodal API products – including our realtime API, our transcription models (Whisper), our speech generation models (TTS), and our image generation APIs (DALLE and native 4o). Collaborate closely with product managers, designers, and other stakeholders to define the strategic vision and product roadmap. Work closely with our research teams to improve our core multimodal models for API customer use cases. Guide technical and architectural decisions, emphasizing scalability, robustness, and user experience. Foster a culture of innovation, continuous improvement, and accountability within your team. Qualifications: Proven experience managing engineering teams that deliver complex, high-quality products at scale. Strong technical background and proficiency in modern software engineering practices and system architecture. Excellent collaboration and communication skills to effectively coordinate across diverse teams and stakeholders. Familiarity with or strong interest in multimoda

awsrestai
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O
OpenAI
📍 San Francisco• Full-time
1mo ago

About the Team Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role We’re looking for a GPU Inference Engineer to contribute to improvements in model serving efficiency for our Robotics research. This is a high-impact role where you’ll drive initiatives to optimize inference performance and scalability. You’ll also be engaged in model design, to help assist our researchers in developing inference-friendly models. This role is critical to scaling the team’s broader goals - it will directly enable leadership to focus on higher-leverage initiatives by building a stronger technical foundation. In this role you will: Perform engineering efforts focused on improving model serving, inference performance, and system efficiency Drive optimizations from a kernel and data movement perspective to improve system throughput and reliability Partner closely with research and product teams to ensure our models perform effectively at scale Design, build, and improve critical serving infrastructure to support Robotics growth and reliability needs You might thrive in this role if you: Have deep expertise in model performance optimization, particularly at the inference layer Have a strong background in kernel-level systems, data movement, and low-level performance tuning Are excited about scaling high-performing AI systems that serve real-world, multimodal workloads Can navigate ambiguity, set technical direction, and drive complex initiatives to completion This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. About OpenAI OpenAI i

awsrestai
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O
OpenAI
📍 San Francisco• Full-time
1mo ago

About the Team The Codex team is responsible for building state-of-the-art AI systems that can write code, reason about software, and act as intelligent agents for developers and non-developers alike. Our mission is to push the frontier of code generation and agentic reasoning, and deploy these capabilities in real-world products such as ChatGPT and the API, as well as in next-generation tools specifically designed for agentic coding. We operate across research, engineering, product, and infrastructure—owning the full lifecycle of experimentation, deployment, and iteration on novel coding capabilities. About the Role As a Performance & Systems Engineer on the Codex team, you will be responsible for whole-system optimization across a complex, evolving stack. Codex spans LLM inference, cloud orchestration, agentic work management, and multiple product surfaces. Your job will be to identify and land high-leverage changes—across infrastructure, modeling, and product layers—that make Codex agents significantly faster and cheaper to serve. We’re looking for generalists who thrive in ambiguity and love chasing performance bottlenecks to ground. This is a high-ownership role where your work will directly improve the experience of millions of users. This role is based in San Francisco, CA. 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: Hunt down and address inefficiencies across the Codex system stack, from agent behavior to LLM inference to container orchestration, and beyond. Build tooling to measure, profile, and optimize system performance at scale. Collaborate with researchers and engineers to land high-ROI changes that improve latency and cost. You might thrive in this role if you: Have experience operating across both ML systems and cloud infrastructure. Enjoy diving into messy, ambiguous problems and emerging with clear wins. Think holistically about performance, balancing spee

awsrestai
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O
1mo ago

About the Team: Compute Infrastructure builds the platform that turns enormous amounts of compute into a reliable engine for frontier AI. We design, provision, schedule, operate, and optimize the systems that connect accelerators, CPUs, networks, storage, data centers, orchestration software, agent infrastructure, developer tools, and observability into one coherent experience for researchers and product teams. Our work spans the entire stack: capacity planning and cluster lifecycle, bare-metal automation, distributed systems, Kubernetes and scheduling, deep system optimization, high-performance networking, storage, fleet health, reliability, workload profiling, benchmarking, and the developer experience that lets teams use enormous compute systems with confidence. At this scale, small improvements to communication, scheduling, hardware efficiency, or debugging workflows can compound into meaningful research velocity. We are hiring across Compute Infrastructure rather than for a single narrow team, and we use this opening to match strong engineers to the problems where they can have the most leverage. About the Role We are looking for engineers who want to build the compute platform behind OpenAI's research and products. You may not be the strongest in low-level systems, high-performance computing, distributed infrastructure, reliability, CaaS, agent infrastructure, developer platforms, tooling, or the user experience around infrastructure. What matters is that you can reason carefully about complex systems, write durable software, and raise the quality and velocity of the people around you. Depending on your background and interests, you might work close to hardware, close to users, on CaaS and agent infrastructure, or on the control planes and data planes in between. You could help bring new supercomputing capacity online, optimize training workloads from profiler traces and benchmarks, improve NCCL and collective communication behavior, reason about GPUs, NICs, t

awskubernetesrest
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O
1mo ago

About the Team The Cooperative AI team is scaling OpenAI with OpenAI. We are building a model-powered scaled automated workforce and knowledge system that evolves and learns alongside a human workforce. By leveraging OpenAI’s state-of-the-art models and technologies, some already in production, others still in the lab, we develop systems that reason and work autonomously for a wide variety of operational work. We leverage real workloads for critical systems across finance, sales, customer support, integrity, product insights, internal operations, and more in order to drive insights into product and industry. We partner closely with internal teams and external customers globally, operating in a hyper-fast feedback loop where many of our users are just a few steps away. This proximity allows us to iterate quickly, validate impact in real time, and accelerate industry impacting learnings and systems builds. We are a highly multidisciplinary, self-contained team focused on transforming the workplace via smart systems, knowledge, scalable and reliable primitives that apply world-class AI capabilities across domains. Our mission is to learn fast and transform how humans collaborate with AI at scale. About the Role We are looking for a hands-on Engineering Manager to lead a small, fast-moving team building AI-powered automation systems that redefine how work gets done across OpenAI. This role sits at the intersection of applied AI, research, and product engineering. You’ll lead a team that builds systems that know how to learn from humans, and carry real workloads across, sales, support, finance, IT, and more, while staying deeply involved in the technical work. You will operate in a highly iterative environment, deploying systems directly to internal users, gathering rapid feedback, and evolving solutions in real time. This is a high-ownership role for someone excited about building 0→1 systems, working closely with customers, and shaping how AI transforms operational wor

awsrestai
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O
OpenAI
📍 San Francisco• Full-time
1mo ago

About the Team The Foundations Research team works on high-risk, high-reward ideas that could shape the next decade of AI. Our goal is to advance the science and data that enable our training and scaling efforts, with a particular focus on future frontier models. Pushing the boundaries of data, scaling laws, optimization techniques, model architectures, and efficiency improvements to propel our science. The Search team sits within Foundations, building agentic search by co-designing model–system interfaces with the core search stack (serving, indexing, retrieval) to translate model intent into reliable, real-world actions. Operating at the frontier of AI and information retrieval, the team develops large-scale systems that transform and index vast corpora, enabling models to reason over global knowledge and act dependably. In close partnership with researchers, we rapidly bring modeling breakthroughs into production and redefine how intelligent systems discover, retrieve, and synthesize information at planetary scale. About the Role We’re looking for a Software Engineer focused on building and scaling retrieval systems. You’ll work with a team of researchers and engineers to develop infrastructure that enables models to retrieve and act on the right information at the right time. This includes designing and operating indexing systems, retrieval pipelines, and serving layers. This work supports retrieval across OpenAI products and research, with direct impact on system performance, reliability, and scale. Responsibilities Build and scale retrieval infrastructure across indexing, serving, and query execution. Develop low-latency, high-throughput systems for real-time model interaction. Partner with research to productionize embedding and retrieval techniques. Support dense, sparse, and hybrid retrieval pipelines. Own system performance, reliability, and observability at scale. Collaborate across Pretraining, Inference, and Product teams to integrate retrieval end-to-e

awsrestai
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N
Notion
📍 San Francisco• Full-time• $230K – $280K/yr
1mo ago

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role: Millions of people use Notion every day, and we’re growing quickly. The Infrastructure Security team’s mission is to build a secure-by-default foundation across Notion’s technical stacks—architecting systems that make the secure path the easy path. As an IC4 on this team, you’ll own meaningful infrastructure security problems end-to-end: from identifying risk, to designing pragmatic controls, to shipping secure defaults that scale across engineering. This role can be based in either San Francisco or New York City. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You'll Achieve: Proactively enhance the security posture of our AWS accounts and cloud infrastructure. Create secure frameworks for secrets management and authentication/authorization. Design and deploy robust Identity and Access Management (IAM) solutions. Provide guidance and education on security and privacy best practices to cross-functional partners. Participate in (and hel

awsrestai
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Notion
📍 San Francisco• Full-time• $213K – $320K/yr
1mo ago

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role Collections Experience owns the product experience for Notion’s database block and everything on top of it: properties, views, forms, permissions, and many more features. If you’ve ever typed /database in a Notion page, you’ve already used something our team built. We’re hiring an experienced software engineer to accelerate our mission to build a flexible, reliable, and intuitive primitive that gives everyone the power to model their work exactly as they imagine— from simple lists to the most complex workflows. We’re 8+ engineers, designers, and PMs across SF and NYC. You’ll work across the stack in TypeScript, ship features that touch both the data model and the UI, and help shape where the database block goes next. What You'll Achieve Design and ship new database properties and views that expand what people can model in Notion Design permission models that hold up at the scale of our largest customers Partner with the Agent team to grow what Notion Agent can do with databases, from tool development to eval-driven iteration Collaborate closely with product and design on features that are ambiguous up front and require

typescriptrestai
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Notion
📍 San Francisco• Full-time• $230K – $260K/yr
1mo ago

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About The Role Millions of people rely on Notion to do their most important work, and protecting that trust is foundational to everything we build. We’re looking for a hands-on Detection Engineer to build and operate the systems and workflows we use to detect and respond to attacks across Notion’s cloud-native environment. You’ll ship high-signal detections, improve the platform that powers them, participate in incident response, and help shape how detection and response engineering scales at Notion. You’ll work closely with Engineering, Corporate Security, and Infrastructure, with broad latitude to identify gaps, prioritize investments, and build what’s needed next. We view detection and response as a software engineering discipline: detections are code, platforms are products, and measurement matters What You'll Achieve Design and maintain high-signal detections across cloud, identity, endpoints, and SaaS environments. Build and improve the detection platform, including rule lifecycle management, tuning, measurement, and rollout safety. Develop tooling and automation that accelerate triage, enrichment, investigation, and detection

awsazuregcp
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Notion
📍 San Francisco• Full-time• $200K – $280K/yr
1mo ago

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role Millions of people use Notion — and this number is increasing every day. That means millions of people, from students to large enterprises, trust us to keep their data secure and private, and we value this more than anything. We want to keep earning trust, while also continuing to amaze our users with the tools they can build in Notion. Notion is looking for software engineers who are excited to make trust and security a core part of how Notion scales. This role can be based in either San Francisco or New York City. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You'll Achieve Build authentication and other product features that make Notion safe and secure by default, helping more people and teams trust Notion for their most important work while supporting growth across consumers and enterprise customers. Build scalable, AI-powered systems to detect, investigate, and mitigate risks across Notion, including phishing, spam, objectionable

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