System Engineering Intern in United States

About the Team The Product & Platform teams at OpenAI are responsible for delivering the company’s most impactful offerings—such as ChatGPT, our API platform, and new enterprise capabilities—to a global and diverse customer base. These systems must perform at scale and deliver exceptional experiences to developers, consumers, and businesses alike. Technical Program Managers at OpenAI play a key leadership role in scaling these efforts, partnering deeply with product, engineering, design, and go-to-market teams to bring ambitious ideas to life and ensure clarity and discipline in execution. About the Role We are hiring a Technical Program Manager to support OpenAI's critical AI deployments across strategic cloud partners. This role is designed for a candidate who can operate as an end-to-end owner across internal engineering teams and external partner organizations. This role will drive the technical strategy and execution required to bring OpenAI models and platform capabilities into partner environments responsibly and at scale. The work spans engineering deliverables, shared roadmaps, model launch pipelines, technical integration, launch readiness, and post-launch follow-through. You will work closely with senior leaders across OpenAI engineering, infrastructure, product, safety, security, legal, finance, and go-to-market, as well as technical counterparts at our partners. The job is to turn broad partnership commitments into concrete execution plans, align both sides on what must land, and build repeatable mechanisms for launching OpenAI capabilities on third-party platforms. 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: Lead end-to-end execution for major cloud partner programs spanning model deployment, product integration, operational readiness, launch follow-through, and partner-platform adoption. Own integrated technical roadma

We are a team of engineers that translate our real-world experience to help our user communities solve problems. With a focus on service management, helping teams respond to incidents, run on-call, and automate their operations, you will work with practitioners and leaders across the industry and broaden your impact to the SRE, Engineer, DevOps, and Operations community at large. This is a unique opportunity to use both your engineering and creative storytelling skills to shape the landscape in cloud observability, incident response and service management. What You'll Do: Act as a subject matter expert for service management (incident response, on-call, IDP, Work Management, Workflow Automation, Agent Builder, and operational automation) for Datadog's advocacy and engineering teams Create content in one or more mediums to build Datadog's reputation as a leader in DevOps, Monitoring, Observability and Security e.g. building demos, public speaking, blogging, documentation, webinars, open source, research reports and more Partner with product engineering teams to build compelling demos, and coach internal engineering teams on effective communication and presentation Interface with open source communities to drive key messaging in the market and develop new integrations for Datadog Contribute to the product through feedback (bugs or product enhancements suggestions), documentation, or code Who You Are: Approximately 5+ years of experience as a Platform Engineer, Site Reliability Engineer, DevOps Engineer or Software Developer with hands-on experience as an on-call/incident responder and running production systems in complex IT environments You have a strong understanding of core service-management practices (incident response, on-call, post incident reviews, and SLOs), using tools like Datadog, PagerDuty, Opsgenie, incident.io, Rootly, Jira Cloud Platform, Cortex, or similar and know how to navigate operational challenges of different s

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE As a member of the Capacity Strategy & Operations team, you will sit at the intersection of supply intelligence, demand forecasting, and cross-functional execution, turning a complex, fast-moving hardware market into a predictable, reliable foundation for our customers and internal engineering teams. This is not a purely analytical role. You will own the end-to-end capacity planning process: from translating customer commitments and growth forecasts into concrete supply requirements, to coordinating fulfillment across vendors, finance, and the infrastructure team, to building the systems that make all of this repeatable and scalable. When supply is constrained and tradeoffs are unavoidable, you are the person in the room who can model the options, make a clear recommendation, and drive alignment fast. You are a strong fit if you have operated at the intersection of strategy and execution before — someone who is equally comfortable building a capacity model in a spreadsheet and running a cross-functional war room when a customer deployment is at risk. EXAMPLE INITIATIVES Demand-Supply Alignment Framework: Build and own the process that translates customer pipeline, signed commitments, and growth projections into a forward-looking GPU demand signal — so the team is never caught flat-footed when a customer scales faster than expected. Constrained Allocation Playbook: Define the decision framework for how Basete

Coordination Systems provides foundational distributed systems building blocks for internal Datadog platforms. Our services cover sharding, consensus, resource protection, configuration distribution, and much more. We are looking for a manager to lead the Coordination Systems - Storage team. This team provides essential configuration storage and distribution systems that are depended upon by almost every service and pod at Datadog. We power critical runtime configuration (e.g. feature flags), complex control planes (e.g. dynamic sharding configuration), and much more. Storage is one of four subteams within Coordination Systems. If successful, the candidate will have opportunities to lead other growing and impactful areas such as Resource Protection. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: (Describe role responsibilities here/max 6 bullets) Lead a core team of 5 engineers (distributed, with majority in NYC) Lead ceremonies, prioritize and delegate project Stay hands-on with the code, e.g. isolated features, small remediations, investigation follow ups Stay actively involved in operations, incidents, root cause analysis, etc. Constantly promote a culture of operational excellence, organizing gamedays, conducting operational reviews, staying proactive with reliability Who You Are: (Describe role qualifications here/max 6 bullets) Strong distributed systems skills, able to understand and account for a variety of failure modes, well-versed in end-to-end o11y, validation testing, simulation setup, etc. Worked on platform teams before, providing critical infrastructure to internal stakeholders Experienced in handling significant incidents, both as a responder and follow-up ow

About the Team At OpenAI, we’re building the connective tissue between our mission and our people. People Innovation Labs is a fast-moving engineering team embedded in the People organization, focused on rethinking how we find and retain the best talent and empower everyone to do their best work. From recruiting to culture, we’re designing systems that give our People Team a significant edge by infusing OpenAI’s models and first-principles thinking into every aspect of our work. Our projects range from greenfield 0-1 products like OpenHouse (our internal knowledge hub) to AI-powered automations and scalable recruiting tools. We’re defining the future of work at OpenAI, creating a blueprint for how AI can supercharge productivity, culture, and innovation. About the Role We are looking for a self-starter engineer who loves building new products in an iterative and fast-moving environment. This team is for full stack product engineers who are deeply curious about culture, recruiting and people development, and want to know everything from the business strategy and metrics down through the code that gets us there. In this role, you will work with members of the People Team and leaders across the company to build software focused on HR, culture and recruiting from the ground up. You’ll also innovate on how we apply LLMs in these domains. In this role, you will: Own the full product development lifecycle for new people products end-to-end Talk to internal stakeholders to understand their problems and design solutions to address them Work with the research team to share relevant feedback and iterate on applying their latest models Collaborate with a cross-functional team of engineers, HRBPs, recruiters, researchers, product managers, designers, and people in operations to create cutting-edge products Your background might look something like: 4+ years of professional engineering experience (excluding internships) in relevant roles at tech and product-driven companies Forme

About the Team OpenAI’s Compute Strategy team is responsible for securing and scaling the core resources that power our research and products. We partner across engineering, finance, legal, and operations to identify, negotiate, and execute strategic partnerships that expand OpenAI’s capacity for compute, power, and data center infrastructure. Our mandate spans energy procurement, real estate development, colocation, cloud service providers, silicon and strategic supply chain, and infrastructure financing—ensuring OpenAI can grow with speed, resilience, and cost-efficiency. About the Role We are hiring several Business Development Lead, Compute Strategy positions focused on compute infrastructure. Each hire will bring deep expertise in one or more focus areas while collaborating across the broader infrastructure stack. In this role, you will source opportunities, structure partnerships, and negotiate high-value agreements across OpenAI’s infrastructure ecosystem. You will work directly with external partners and suppliers while collaborating internally with engineering, legal, finance, and operations to ensure we have the resources needed to support state-of-the-art AI systems. This role requires technical fluency, commercial judgment, and disciplined execution. Your work will directly shape how quickly, reliably, and efficiently OpenAI can bring new compute capacity online. Each hire will focus on building partnerships and executing deals in one or more of the following areas: Energy and Power: securing scalable and sustainable energy supply. Land and Real Estate: identifying and securing strategic sites. Colocation : evaluating and contracting for third-party data center capacity. Cloud Service Providers (CSPs): structuring partnerships with hyperscalers and specialized AI cloud providers. Silicon: building semiconductor partnerships to secure advanced silicon and resilient long-term supply. Fiber & Equipment: securing fiber & critical data center equipmen

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: Airbnb’s mission is to create a world where people can Belong Anywhere. As we work to achieve that mission, we’re building world-class learning experiences for our technical teams. We’re looking for an exceptional and creative individual inspired to deliver innovative learning experiences that have tremendous organizational impact. The Difference You Will Make: The Staff Program Manager, Technical Education will play a key role in executing various technical learning programs including our Engineering Education programs that currently focus on AI Education, and other engineering and data education programming. Our focus is on impact and experimentation, creating world-class programs that enable technical excellence. We’re employing best practices from learning science and using measurement to iterate on learning experiences. The ideal candidate is confident in their ability to develop scalable learning experiences that drive overall growth and development for our technical audience. We are looking for someone who has the ability to synthesize a range of concepts into unified experiences, stay up to date in a rapidly shifting technical ecosystem, establish systems and processes, and deliver top notch program management. A Typical Day: Collaborate on and develop program strategy for various technical programs, including AI Enablement, AI Education, Machine Learning Education, Data Education, Engineering Education with internal SMEs and other Technical Learning & Development team members Design, create content, and project manage in-person and virtual technical learning

Applied AI is where Datadog's ambitious AI bets get built and shipped ( Bits Chat , updog ). We sit at the intersection of research and product: turning promising capabilities from Datadog AI Research lab and the research community into production systems that reach real customers. The team builds the foundations for agentic systems capable of operating at scale in complex production environments. Current bets span agents that run autonomously at scale, context and memory layers that make those agents more intelligent over time, and tools that help customers build and validate AI-native services in production. The mandate is to move fast from idea to customer impact, and when a product finds its footing, to set it up for growth. As an Engineering Manager I in Applied AI, you will lead a team of engineers and applied scientists working on one of these challenges. You will define technical direction, run short feedback loops, make deliberate decisions about what to pursue or stop, and work closely with product managers, research teams, and cross-functional partners to ship AI capabilities that matter. At Datadog, we place value in our office culture, the relationships and collaboration it builds and the creativity it brings. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do Lead and develop a team of engineers and applied scientists focused on building the foundations for agents operating at scale Work closely with product managers, research teams, and cross-functional partners to shape the team's bets from initial framing through to broader adoption, with a clear definition of success criteria at each stage Own end-to-end delivery of high-quality AI systems, from early research exploration to production-grade reliability, with high standards for operational excellence, system reliability, and technical quality Navigate the unique challenges of shipping AI-powered products: balancing quali

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. About the Role The Product Platform Tools team builds and operates Cloudflare's internal support and admin platform - the foundation that customer-facing and operational teams across the company rely on to do their jobs. As a Systems Engineer on this team, you'll design and build the backend services, infrastructure, APIs, and integrations that power this platform at enterprise scale, working closely with both engineering teams and non-engineering

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for PhD research interns with strong research experience in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. This internship is well suited to candidates interested in improving existing methods and developing new techniques for large-scale model training, optimization, and inference, extending models to long-context and long-horizon tasks, and improving inference-time efficiency, reliability, and robustness in high-stakes real-world deployments. Preferred Qualifications: Currently pursuing a PhD in computer science, machine learning, or a related field. A demonstrated record of research in reinforcement learning, machine learning, foundation models, or related areas. Experience developing and evaluating large-scale models or machine learning systems. Familiari

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. Check out our Engineering Blog and Emerging Talent Blog for more on our tech stack, mission and values! About the Role Ramp is, at its core, an engineering company, and is on a mission to build the best engineering team in NYC and SF! We are rapidly scaling our mobile app, and our ideal candidate will contribute to building the next iteration of Ramp on Mobile with our world-class team. We are looking for an Android intern for our 12 or 16-week Fall Program (August/September 2026 - December 2026) who is excited to be a part of our early story and help us build a diverse and vibrant tech community. We hire engineers with a broad set of technical skills who are highly cross-functional and eager to solve a wide range of engineering challenges. Our ideal candidate has a strong sense of ownership and enjoys owning projects from inception to scaling them in production. We value people who take pride in their work and show an aptitude for learning quickly, whether they’re familiar with our stack or not. As an intern, you’ll be working with a nimble team of

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're looking for Forward Deployed Engineers on our engineering team who want to work at the intersection of deep infrastructure work and direct customer impact. As an FDE, you'll partner with leading AI companies and foundation labs on cloud architecture, networking, storage, containerization, sandboxing, and more — helping them design and ship production infrastructure on Modal's platform. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the infrastructure stack, and energy for working directly with customers on hard problems. You will: Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and deploy massive-scale production workloads on Modal Lead technical discovery and architect

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

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 The Mission The Foundry is ClickUp's internal AI innovation lab — embedded inside GTM Systems and accountable for turning AI capabilities into production-grade, internally deployed products that make every GTM function faster and smarter. We build the infrastructure that powers AI-first work across Sales, Marketing, Post-Sales, and Revenue Operations. As the Senior Software Engineer on this team you will own the technical delivery of our MCP server platform, agent orchestration layer, and internal tooling — shipping production systems used daily by hundreds of ClickUp employees, and scaling your own throughput by treating AI tools as first-class engineering collaborators. What You'll Own MCP Server Platform Design, build, and operate Model Context Protocol servers that expose CRM, ticketing, analytics, and communication data to AI agents across the GTM stack Implement Okta PKCE authentication flows and RBAC policy enforcement so agents access only the data they're authorized to touch Maintain deployment infrastructure on AWS (Bedrock, Lambda, ECS, API Gateway) and contribute to GCP workloads where applicable Own observability: structured logging, distributed tracing, latency SLOs, and on-call runbooks for every production server Agent Orchestration & AI-Native Products Build and maintain multi-step autonomous agents that execute end-to-end GTM workflows — lead qualification, deal room assembly, onboarding automation, support triage, and more Architect prompt engineering frameworks, tool-call schemas, and agent evaluation harnesses that make AI behavior predictable and auditable Integrate with LLM p

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, Washington D.C., London and Amsterdam. Plaid's Infrastructure team builds the platforms and tooling that help engineering teams develop, deploy, and operate production systems safely. Release Engineering owns the path from merge to production, including Plaid's zero-touch deployment system, progressive rollouts, metric-gated analysis, and automatic rollback. Our goal is to make safe shipping the default for every product team. As a Staff Site Reliability Engineer on Release Engineering, you'll define and scale Plaid's reliability practices across product engineering. You'll architect our SLO and error-budget programs, drive the adoption of progressive delivery, and ensure new products are production-ready. By partnering across product and platform teams, you'll translate complex production needs into intuitive, self-service tooling. This is a hands-on technical leadership role where you'll shape the future of our deployment systems—ensuring they remain fast and safe even as AI-assisted development increases code velocity. What excites you Lead the expansion of reliability standards across product engineering, converting foundational infrastructure into lasting operational habits and tooling. Architect and manage the SLO and error-budget