Software Engineer Infrastructure in United States

About the Team Customer education helps customers and partners build the practical skills and confidence to use AI and OpenAI products safely and effectively. The team focuses on role- and skill-based learning paths, practical content, and product experiences that accelerate learning in the workplace. It brings together learning and enablement expertise, field insight, product signals, and measurement to improve learner and business outcomes. Together, these experiences will help enterprise users build practical AI skills, apply them with confidence in their work, and demonstrate what they can do. Employers will gain a clearer view of workforce skills and progress, helping them recognize capability, focus development where it matters most, and build confidence in workforce readiness. About the Role We’re looking for a full-stack engineer to define and build a new class of learning experiences. This is an early-stage product area where technical judgment, product sense, and learner empathy are critical. You will be setting a technical vision for how people use AI to learn how to use AI, safely and beneficially. This is a hands-on, 0-1 product engineering role with broad technical and product ownership. You’ll set direction, make foundational decisions, and ship the first versions of experiences that can grow into the default way people learn at work. You will drive full-stack product experiences end to end, from prototype through launch, instrumentation, iteration, and production hardening. The work spans interaction design, frontend implementation, backend APIs and services, learner state, content and runtime integration, telemetry, evaluation, reliability, safety, accessibility, and launch readiness. You’ll work closely with our education, GTM, and engineering teams to translate how people learn into products people want to use. bring role- and skill-based learning paths into the product, designing coaching, feedback, and adaptive support which responds to each lea

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. Plaid’s mission is to unlock financial freedom for everyone by making money movement and access to financial data simple and secure. As a Software Engineer, you will design and build the systems that power how millions of people connect to their finances. You will work across the stack, from reliable backend services and APIs to intuitive applications that bring those systems to life. You will collaborate with engineers, product managers, and designers to ship products that make financial services more accessible and transparent. At Plaid, engineers take ownership early, grow quickly, and see their work reach millions of users. Responsibilities: System Design & Development: Build and maintain scalable, reliable backend or fullstack systems and APIs that power Plaid’s products. Collaboration: Work closely with product managers, designers, and other engineers to define and deliver features that solve real customer problems. Code Quality: Write clean, efficient, and well-tested code. Participate in reviews to maintain high engineering standards. Testing & Debugging: Build automated tests, monitor system performance, and troubleshoot issues in production environments. Continuo

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. Plaid’s mission is to unlock financial freedom for everyone by making money movement and access to financial data simple and secure. As a Fullstack Software Engineer, you will design and build the systems and experiences that power how millions of people connect to their finances. You will work across the stack, building scalable backend services and APIs while also crafting intuitive, high-quality frontend experiences that bring those systems to life. This role is ideal for engineers who enjoy switching between backend problem-solving and frontend user experience work, and who are excited to grow their impact across both. You will collaborate closely with product managers, designers, and other engineers to ship products that are reliable, secure, and delightful to use. At Plaid, engineers take ownership early, contribute to architectural decisions, and see their work reach millions of users. Responsibilities: Design & Development: Design, develop and maintain both frontend and backend components Majority Backend Focus (60-70%): Develop APIs and services, focusing on scalability, security and performance. Frontend Focus (30-40%): Build delightful experiences using modern JavaS

About the Team The Safety Systems org is responsible for various safety work to ensure our best models can be safely deployed to the real world to benefit the society and is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. The Safety Engineering team builds the platforms and tools that make OpenAI’s models safe to use in the real world. We partner closely with researchers, product teams, and policy to turn safety ideas into reliable, scalable systems: measuring risk, enforcing safeguards, and continuously improving how models behave in production. Our work sits at the intersection of product engineering, data, and AI, and directly shapes how millions of people experience OpenAI’s technology. About the Role We’re looking for a self-starter engineer who loves building products in an iterative, fast-moving environment—especially internal tools that unlock real-world impact. In this role, you’ll build full-stack tooling for our Safety Systems teams that directly improves the safety and reliability of OpenAI’s models, including in sensitive areas like mental health and other vulnerable-user protections. Your work will increase the team’s velocity in identifying and fixing safety issues and help tighten the feedback loop between policy, data, and the model training cycle. In this role, you will: Own the end-to-end development of internal tools that help improve the safety of OpenAI’s models (with a focus on areas like mental health and other vulnerable-user protections) Partner closely with Safety Systems researchers, engineers, and model policy creators to understand workflows, pain points, and requirements—and translate them into durable product solutions Build full-stack experiences to support core model policy workflows, such as labeling and inspecting data, analyzing and reviewing failure cases, and surfacing insights for iteration Optimize internal applications f

About Mixpanel Mixpanel is the leading product intelligence and analytics platform, trusted by more than 29,000 companies to help understand how people use the products they build. By combining powerful analytics with AI that knows your business, Mixpanel helps teams see what’s working, diagnose what’s not, and decide what to build next. Learn more at mixpanel.com . About Mixpanel Mixpanel turns data clarity into innovation. Trusted by more than 29,000 companies, including Workday, Pinterest, LG, and Rakuten Viber, Mixpanel’s AI-first digital analytics help teams accelerate adoption, improve retention, and ship with confidence. Powering this is an industry-leading platform that combines product and web analytics, session replay, experimentation, feature flags, and metric trees. Mixpanel delivers insights that customers trust. Visit mixpanel.com to learn more. About The Team Mixpanel Engineering is a small, fast-moving team focused on delivering real value to customers. We build powerful AI-powered product analytics while obsessing over clarity, simplicity, and delight. Engineers here own problems end to end. You can move across the stack to ship impact without being blocked by silos or heavy process. Product innovation drives our business, and product engineering teams own that responsibility. Our OLAP engine queries over 500 trillion events; a typical blob storage system we interact with processes 300 PiB/month at 1.2 Tbps sustained, and we run many of them across the world. The Data Runtime team owns the data execution layer that powers every Mixpanel product. We ensure that every customer query runs fast, cheap, and reliably, at any scale. This is an exciting time to join. Mixpanel's agentic and AI-first products are driving rapid growth in query volume, and Data Runtime is making the big bets that power it. We’re investing in elastic query compute and a distributed file cache that will let us scale query workloads dramatically without scaling cost with them. We

About the Team The Astral team builds high-performance developer tools to power the future of programming, at OpenAI and beyond, including Ruff, uv, and ty. The Astral toolchain sees hundreds of millions of installs per month and powers hundreds of millions of package downloads per day for the Python ecosystem. As a team, we are building on those foundations to continue solving impactful tooling problems as programming evolves. About the Role We are looking for an experienced software engineer to build next-generation programming language tooling. If you like writing high-performance Rust, it could be a good fit; if you like thinking about the future of programming, it could also be a good fit. Strong candidates tend to have deep experience with Rust, Python, open source, compilers, or developer tools — but few candidates are deep in all of these areas, and we've hired candidates without prior Rust or Python experience. In this role, you will: Design and implement features in Astral’s existing open source projects (Ruff, uv, ty, and python-build-standalone, and more). Support Astral’s open source projects as a maintainer, triaging user issues, reviewing pull requests, and participating in community discussions. Evolve the Astral toolchain to accelerate development velocity at OpenAI. Build entirely new tools, in entirely different programming ecosystems, to power the future of agentic software development. Your background might look something like: 5+ years of professional engineering experience, excluding internships, in relevant engineering roles. High agency and comfort operating in a fast-moving environment, with strong ownership of security, reliability, and operational excellence. Strong developer empathy and communication skills, including experience maintaining open source projects. Exceptional systems engineering fundamentals and a track record of leading complex projects from ambiguous problem statements through to user impact. Proficiency in one or more s

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Software Engineer II Overview Join a team focused on transforming how Mastercard's payment systems are built, scaled, and operated. As a Software Engineer II, you will design and develop cloud-ready applications, microservices, and APIs that support large-scale payment processing platforms while helping advance modernization, automation, and engineering excellence across the organization. You'll work on scalable backend systems, contribute to platform modernization initiatives, and collaborate with engineers to deliver reliable software solutions. This role is ideal for someone who enjoys solving technical challenges, building production-ready applications, and continuously improving how software is designed, developed, tested, and supported. What You Will Do •Design software components by translating product requirements into scalable technical solutions. •Contribute to software architecture decisions and technical design discussions. •Build modular, extensible, maintainable, and performant applications. •Design, execute, and maintain unit, functional, and integration tests. •Apply secure coding practices throughout the software development lifecycle. •Participate in code reviews and contribute to engineering quality standards. •Support system performance optimization, scalability impr

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Software Engineer II Overview Who is Mastercard? Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all. The Fraud Products team (part of O&T) is developing new capabilities for MasterCard's Decision Management Platform, which serves as the core for multiple business solutions to combat fraud and validate cardholder identity. Our patented Java-based platform processes billions of transactions per month in tens of milliseconds using a multi-tiered, message-oriented approach for high performance and availability. MasterCard software engineering teams leverage Agile development principles, advanced development, design and test automation practices, and an obsession over security, reliability, and perfo

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Software Engineer II Who is Mastercard Mastercard is a global technology company in the payments industry. We work to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart and accessible. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. About the Role We are hiring a Software Engineer II to join Mastercard's Core Payments department, responsible for delivering solutions that facilitate billions of secure transactions between issuers, acquirers, and service providers worldwide. This role offers the opportunity to contribute to highly scalable, mission-critical platforms that power global commerce. We are seeking a software engineer who is passionate about software development, system quality, and continuous improvement, with a strong focus on delivering reliable, maintainable, and secure solutions. Role Software Development & Design • Design, develop, test, and maintain high-quality J

Job Requisition ID # 26WD100611 Position Overview Autodesk is a global leader in design and make technology, with expertise across architecture, engineering, construction, design, manufacturing, and entertainment. Our software and services empower innovators everywhere to solve challenges big and small—from greener buildings to smarter products to more compelling media and entertainment. At Autodesk, we believe that when you have the right tools to work and think flexibly, you have the power to transform what actually needs making. We provide our customers with technology to help them achieve better outcomes for their products, businesses, and the world. We are looking for a highly motivated software engineer to join the PSET-Access group. The team builds and operates systems that enable secure, reliable, and scalable access to product capabilities and resources, and now in the process to develop the next generation to modernize the access management capabilities. In this role, you will work with engineers and cross-functional partners to design, build, test, deploy, and operate production software. You will primarily develop backend services using Java or Go, while owning well-defined components and projects, contributing to technical decisions, and helping improve the reliability, maintainability, and developer experience of the systems the team owns. This is a strong opportunity for an engineer who has solid software engineering fundamentals and is ready to grow their technical depth and ownership. Responsibilities Design, implement, test, deploy, and maintain production-quality backend software, prim

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 build the model runtime within the inference engine that executes complex, frontier models at scale on OpenAI’s custom silicon. The runtime will sit between models running on the hardware and the upper layers of the cluster serving software stack, translating demanding inference workloads into efficient execution while optimizing for throughput, latency, utilization, and reliability. You will work across model architecture, distributed systems, compilers, kernels, and silicon to design a production-grade runtime comparable in ambition to systems such as vLLM and SGLang, but customized and optimized for OpenAI’s AI accelerator. Your work will shape how new model capabilities map onto the platform and how quickly custom silicon can deliver meaningful performance in production. In this role, you will: Design and implement the LLM inference runtime for frontier models running on custom silicon. Build scheduling, continuous batching, memory management, KV-cache management, and execution orchestration for high-performance inference. Develop distributed execution strategies across chips, hosts, and racks, including model partitioning, communication, and synchronization. Optimize end-to-end latency, throughput, memory efficiency, and hardware utilization across diverse model architectures and serving workloads. Partner with kernel, compiler, architecture, and silicon teams to co-design interfaces and remove performance bottlenecks across the stack. Enable new

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 build the low-level device runtime that turns compiled programs into efficient, functional and performant execution on OpenAI’s custom AI accelerator. This software will schedule kernel launches, manage device memory and address spaces, coordinate synchronization, and expose reliable abstractions to higher-level runtimes and frameworks. You will work at the boundary of software and hardware, partnering with compiler, kernel, architecture, verification, and silicon teams to define interfaces and validate behavior. You will also use and improve event-based, cycle-accurate simulation to develop runtime capabilities before silicon is available, diagnose performance and correctness issues, and guide hardware-software co-design. In this role, you will: Design and implement the low-level device runtime for OpenAI custom silicon. Build kernel-launch scheduling, command submission, queueing, dependency tracking, and completion handling. Manage device memory spaces, allocation, virtual-to-physical mappings, data movement, and lifetime across concurrent workloads. Implement synchronization primitives, events, barriers, streams, and ordering guarantees that are correct and efficient. Define clean interfaces between the runtime, drivers, firmware, compiler-generated code, kernels, and higher-level execution systems. Use event-based, cycle-accurate simulators to develop, validate, debug, and performance-tune runtime behavior before and after silicon availability. Di

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: As a Developer Platform engineer, you will directly contribute to the foundational pieces that make Notion extensible and connected. You will build tools, APIs, and platform experiences that help customers connect Notion to the world — bringing their apps, data, and workflows into one workspace. Your work will make it easier for developers, admins, and builders to create reliable integrations and automations on top of Notion. You will be a key player in building the robust technical foundation that allows Notion to achieve the connected workspace vision. Your work will include both internal platform contributions that accelerate other Notion engineering teams and end-user-facing functionality that enables toolmaking ubiquity. You will be presented with challenging technical problems, as Notion’s product needs are complex. You’ll play a key role in identifying and executing against technical investments that ensure the long-term quality, reliability, and performance of Notion’s platform as we scale. This role can be based in either San Francisco or New York City. We work from our offices on Mondays, Tuesdays and Thursd

Software Engineer - DevSecOps (Senior or Lead) — USA - Tukwila, WA. Apply via Workday.

About the Team Our mission at OpenAI is to discover and enact the path to safe, beneficial AGI. To do this, we believe that many technical breakthroughs are needed in generative modeling, reinforcement learning, large-scale optimization, active learning, and other areas. The team builds the performance-critical systems that allow OpenAI's models to run efficiently across a diverse set of AI accelerators. We work across the inference stack, from low-level kernels and compilers through model execution, to unlock the full capabilities of the underlying hardware. About the Role As a Software Engineer, Trainium, you will help bring OpenAI's inference workloads to AWS Trainium and build the software stack required to run cutting-edge frontier models efficiently on the platform. This is a deeply technical, cross-stack role spanning kernels, compilers, and model execution. You will work on the systems needed to support OpenAI's inference stack on Trainium, including developing and optimizing high-performance kernels, improving compiler support, and enabling efficient execution of the model forward pass. You'll work closely with engineers across inference, compilers, kernels, and ML systems to identify performance bottlenecks and build the software needed to take full advantage of Trainium. The work may range from low-level hardware-specific optimization to compiler and runtime improvements to integrating new model architectures into the inference stack. If you enjoy working at the intersection of ML systems, compilers, kernels, and accelerator hardware, this role is for you. We're looking for engineers who are self-directed, comfortable operating across abstraction layers, and excited to solve challenging performance problems for frontier-scale AI systems. In This Role, You Will Build and optimize OpenAI's inference stack for AWS Trainium. Develop high-performance kernels for critical model operations and workloads. Extend and improve compiler support to efficiently target