System Ip Rtl Design Lead in United States

We're on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scale—trillions of data points per day—allowing for seamless collaboration and problem-solving among Dev, Ops and Security teams globally for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. The Team: As organizations rapidly invest in AI applications and build out AI labs, telemetry volumes are growing exponentially and costs are becoming unpredictable. From LLM interactions to agentic workflows, AI systems generate unpredictable streams of logs, driving up costs and making it harder to maintain efficient observability. These challenges are critical for organizations in regulated industries with strict data residency requirements, where data must remain within controlled environments. Datadog’s Bring Your Own Cloud (BYOC) team is reimagining what observability and security look like at petabyte scale in the AI era. The Opportunity: The Group Product Manager - Bring Your Own Cloud (BYOC) role is responsible for defining and bringing to market the next generation of telemetry analytics and insights capabilities in an AI-first environment. This role is highly technical and creative in nature as you will envision novel ways to enable customers to cost-effectively explore, analyze and report over petabytes of data through a welcoming and easy-to-use interface. You will partner with various teams to take advantage of BitsAI capabilities and surface critical insights on volume usage and retention for popular use cases. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. 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 grow a team

We’re looking for Software Engineering Interns to help build and scale the systems that power Datadog’s observability and security platform. Interns contribute directly to real-world engineering challenges across backend, frontend, infrastructure, data engineering, and developer tooling while working alongside experienced engineers and mentors. You’ll help design, build, and improve systems that process and analyze massive volumes of metrics, logs, and application data in real time. Whether you’re interested in distributed systems, Kubernetes, AI-powered products like Bits AI, or developer platform tooling, you’ll work on meaningful projects that deliver impact to customers at global scale. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Contribute to production systems that process and analyze large-scale observability and application data in real time Build and improve distributed systems across backend infrastructure, developer platforms, and cloud-native services Help identify and solve performance, reliability, and scalability challenges in critical services supporting Datadog’s growing customer base Own and deliver technical projects from design through deployment with support from experienced engineers and mentors Develop technical expertise through hands-on experience with technologies such as Kubernetes, distributed systems, and cloud-native infrastructure Collaborate with fellow interns, mentors, and engineers while building software that delivers impact at global scale Who You Are: Pursuing a degree in Computer Science, Software Engineering, or a related technical field, or have equivalent practical experience Targeting a 2028 full-time start date Demonstrate strong computer science fundamentals, including data struc

The opportunity Datadog’s Infrastructure products help engineers understand and operate the systems their applications depend on. Our customers work in complex environments like Kubernetes and serverless, where infrastructure changes constantly, information is dense, and decisions about reliability, performance, and cost are closely connected. We’re looking for a Staff Product Designer to join Modern Compute, with an initial focus on Containers Autoscaling. Autoscaling helps engineering teams make better decisions about how their applications and infrastructure use resources. Designing these experiences requires making deeply technical systems understandable, helping customers act with confidence, and fitting into the tools and workflows they already use. The team is rethinking how workload and cluster autoscaling come together as a more coherent product experience. This includes how customers get started, understand recommendations, evaluate value, and safely apply changes across their environments. The work also connects to other parts of Datadog, including observability, Cloud Cost Management, permissions, and AI-assisted workflows. As a Staff Product Designer, you will help define that direction and lead the work from early problem framing through shipped product. You will partner closely with product and engineering, bring a high level of interaction and visual craft to complex workflows, and help raise the quality of design across Modern Compute. At Datadog, we place value in our office culture, the relationships and collaboration it builds, and the creativity it brings to the table. We operate as a hybrid workplace to help our Datadogs find a work-life rhythm that works for them. What you’ll do Lead end-to-end product design for Modern Compute, initially focused on our Autoscaling product. Help define the product direction for an area that is still evolving, from early framing and exploration through detailed design and delivery. Design clear, trustwort

As the Senior Product Manager for the Actions & Automations team, you will own the ecosystem that enables customers, partners, and Datadog teams to build, deploy, and operate AI agents on Datadog. You will drive the strategy and execution for the platform capabilities, developer experience, integrations, and extensibility model that make Datadog the best place to build agents that understand and act on production systems. Modern engineering organizations are entering a new era where software is not only monitored and operated by humans, but increasingly by AI-powered agents. As agentic workflows reshape how teams build, operate, secure, and troubleshoot systems, customers need a platform for creating specialized agents, connecting them to business and engineering systems, governing their behavior, and extending them to solve unique organizational problems. You will define and build the ecosystem that makes this possible. Agent Builder sits at the intersection of Datadog's products, AI capabilities, and ecosystem strategy. You will have the opportunity to work across the breadth of the Datadog platform, partner with teams throughout the company, and help establish Datadog as the foundation for operational AI. At Datadog, we place value in our office culture, the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Define the vision, strategy, and roadmap for Datadog's Agent Builder platform and ecosystem. Own the core platform capabilities that enable customers and partners to create, customize, deploy, and manage AI agents. Drive the extensibility model for agents, including integrations, tools, actions, context sources, APIs, SDKs, and developer workflows. Shape how agents perform actions across Datadog products and third-party systems. Partner closely with AI, platform, infrastructure, and product tea

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . The Conversion Visibility Modeling team enables a performant ads marketplace and helps prove value to advertisers by connecting Pinterest onsite activity with conversions that happen offsite (both digital and physical) in a privacy-preserving way. As a Machine Learning Engineering Manager on this team, you will lead a hybrid team of ML engineers and backend software engineers to build end-to-end identity and conversion visibility solutions across modeling, serving, and data infrastructure, so advertisers retain accurate, privacy-aware performance visibility as signals fragment and degrade. You will set the technical direction for high-impact ML systems that feed ranking, bidding, measurement, and reporting across Pinterest’s ads stack. What you’ll do: Attract, hire, develop, and lead a hybrid team of ML engineers and backend softwar

About the Team The GTM Intelligence Solutions team builds the data and decision systems that help customer-facing teams take the right action at the right time. We combine product telemetry, commercial data, customer context, and field activity to identify account health and opportunity, recommend actions and use cases, deliver intelligence through field-facing products and agent workflows, and measure what happens next. We’re looking for a Data Scientist to help build the next generation of GTM intelligence at OpenAI. You will own a flexible portfolio of high-impact decision data products and work closely with Technical Success and other GTM teams to ensure the work drives better decisions. About the Role As a Data Scientist on GTM Intelligence Solutions, you will define and build the intelligence systems that help customer-facing teams prioritize accounts, identify risks and opportunities, choose interventions, and understand what worked. You will set the roadmap and methodology, build canonical features, ship reliable production workflows, monitor quality and adoption, and improve the systems using field feedback and business outcomes. This role combines hands-on technical depth with strong product and business judgment. You should be as comfortable writing production Python and advanced SQL, defining durable data contracts, and operating decision products as you are evaluating a ranking approach or designing an experiment. You will personally ship reliable first versions and partner with Analytics Engineering and Data Engineering when work requires shared infrastructure or additional scale. In This Role, You Will Set the roadmap and methodology for GTM intelligence and decision products, using deep stakeholder discovery to probe beyond stated requests, uncover the underlying decisions, workflows, constraints, and measures of success, and translate them into measurable systems. Own the full lifecycle of intelligence products, including feature definition, methodo

About the Team OpenAI is building Procurement of the future: one that uses AI-enabled systems, clean data, and scalable processes to help the business absorb increasing complexity, speed, volume, and throughput — while enabling teams across OpenAI to operate more strategically and at greater scale. The Hardware Procurement Operations team supports the operational flow of goods and hardware purchasing across OpenAI's hardware business units. We help teams turn business needs into controlled, accurate, and executable procurement activity, from request intake through purchase orders, supplier coordination, change management, receiving readiness, and downstream invoice support. As OpenAI scales, we are building procurement operations that can support changing hardware needs, new business unit priorities, and increasing operational complexity. That means creating practical standards where they help, preserving flexibility where the business requires it, and continuously improving how requests, suppliers, POs, data, and controls move through our systems. About the Role As a Senior Manager of Procurement Operations focused on Hardware, you will own procurement operations for one or more assigned hardware business units. You will be the day-to-day DRI for hardware and goods procurement activity, leading work from intake through purchase requests, POs, supplier needs, changes, receiving readiness, and operational escalations. This is a hands-on operator-builder role for someone who understands the practical complexity of hardware and goods procurement and can both run the work and redesign how the work gets done. You will keep work moving while improving the operating model through better systems, workflows, automation, AI-enabled processes, controls, metrics, and operating leverage. You will evaluate how people, process, policy, systems, data, fiscal controls, and accounting practices come together, and you will work closely with other Central Procurement and BU Procurement

About the Team The Codex Web Layer team provides the web-based systems and user experiences for Codex across the entire stack, from the Electron-like application framework that powers the application, to the user-facing in-app browser. About the Role In this role, you will be responsible for designing and implementing infrastructure and features end-to-end for the Codex desktop client application. You will help define what it means to be a hybrid agentic/interactive web browser. The team embodies “full stack” development from the lowest-level OS integration to the highest-level interaction design. This role is based in San Francisco. 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: Partner closely with product and design to conceive, design, and build features for Codex web browsing features on macOS and Windows. This role will focus mostly on the backend C++ layer and Chromium, but many features cross the full stack including some TypeScript. Partner with the wider Codex team to deliver a high-performance, stable, and secure application platform for client development. This includes API design and implementation (mostly in C++) and the infrastructure that supports deploying it (in Python, TypeScript, and agentic skills). Work with a small, experienced team of engineers on this critical and rapidly growing product. You might thrive in this role if you: Have significant experience building technically complex features end-to-end. Are a strong C++ developer, especially with experience in browser environments like Chromium and Electron. Since this role is more backend focused, general knowledge of web development and TypeScript is helpful but not required. Thrive in a fast-paced, ambiguous environment. Communicate clearly and concisely across many different roles in the organization. Are self-directed, identifying important work and executing it end-to-end. About OpenAI OpenAI is an AI

About the Team The Agent Infrastructure team at OpenAI is responsible for building systems that enable training and deployment of highly useful AI agents, both internally and for the world. We work hand-in-hand with researchers to design and scale the environment in which agentic models are trained – providing a workspace for AI models to execute code, debug issues, and develop software just as human SWEs do. Our training environment for agentic models operates at an extremely high scale and has the flexibility to emulate any environment in which an agent might work. At the same time, our team builds and maintains OpenAI’s core platform for the deployment and execution of agents in production. Our systems power products such as Codex, Operator, tool use in ChatGPT, and future agentic products. Some of the most challenging technical problems in scaling the capabilities and utility of agents and agentic models lie in the infrastructure layer – and our team is focused on building the research and production systems that enable OpenAI to train the most capable models in the world, and maximize the utility of our agentic products for users around the world. About the Role As a Software Engineer on the Agent Infrastructure team, you will have the opportunity to work closely with both research and product at OpenAI - building and scaling systems to train highly capable agentic models, and building the platform and integrations to launch new agents to hundreds of millions of users worldwide. Your work will consist of both building new capabilities - standing up the infrastructure and integrations needed to train more complex agentic models - and rapidly scaling these new capabilities to some of the largest compute clusters in the world. At the same time, you’ll be instrumental to the launch of agentic products at OpenAI - building, maintaining, and scaling the production platform on which all agents run. We’re looking for people with deep experience building AI infrastructu

About the Team The Alignment team at OpenAI is dedicated to ensuring that our AI systems are safe, trustworthy, and consistently aligned with human values, even as they scale in complexity and capability. Our work is at the cutting edge of AI research, focusing on developing methodologies that enable AI to robustly follow human intent across a wide range of scenarios, including those that are adversarial or high-stakes. We concentrate on the most pressing challenges, ensuring our work addresses areas where AI could have the most significant consequences. By focusing on risks that we can quantify and where our efforts can make a tangible difference, we aim to ensure that our models are ready for the complex, real-world environments in which they will be deployed. The two pillars of our approach are: (1) harnessing improved capabilities into alignment, making sure that our alignment techniques improve, rather than break, as capabilities grow, and (2) centering humans by developing mechanisms and interfaces that enable humans to both express their intent and to effectively supervise and control AIs, even in highly complex situations. About the Role As a Research Engineer / Research Scientist on the Alignment team, you will be at the forefront of ensuring that our AI systems consistently follow human intent, even in complex and unpredictable scenarios. Your role will involve designing and implementing scalable solutions that ensure the alignment of AI as their capabilities grow and that integrate human oversight into AI decision-making. This role is especially well suited for someone who can move from an ambiguous model-behavior question to a concrete experimental setup: formulate the hypothesis, build the evaluation or intervention, run the experiment, analyze the result, and decide what the evidence supports. This role may be based in San Francisco or London, subject to team needs and location approval. In this role, you will: We are seeking research engineers and res

About the Team The Stargate organization is responsible for building and scaling the physical infrastructure systems that power OpenAI’s next generation of AI training and inference platforms. This includes the manufacturing, deployment, and operational execution required to bring large-scale compute infrastructure online globally. The team operates at the intersection of data center infrastructure, hardware manufacturing, supply chain, deployment operations, and systems planning. We partner closely across Infrastructure Strategy, Manufacturing Operations, Capacity Planning, Supply Chain, Deployment, and Engineering to execute one of the largest infrastructure scale-outs in the industry. About the Role We are seeking a Technical Program Manager, Rack Delivery to drive operational execution across rack manufacturing, site readiness, and deployment coordination for Stargate infrastructure programs. This role will serve as a key connective layer between manufacturing partners, deployment teams, and infrastructure readiness programs to ensure rack production and delivery timelines remain aligned with site availability and deployment sequencing. You will help manage operational execution across contract manufacturers (CMs), support build planning and RCCA processes, and coordinate deployment readiness across multiple concurrent infrastructure programs. You will also partner closely with Demand Planning teams to translate strategic planning inputs into actionable SKU-level manufacturing and delivery schedules. This role is ideal for someone who thrives operating across ambiguity, manufacturing operations, infrastructure deployment, and large-scale cross-functional execution. 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 support. Key Responsibilities Drive cross-functional coordination between rack manufacturing, deployment operations, and site readiness programs. Manage operational execution acros

We’re looking for a Software Engineer to architect and build backend systems that enforce data privacy and automate compliance at scale. You’ll work closely with product, infrastructure, security, and legal teams to embed privacy-by-design into our data and access layers. This is a hands-on, high-impact role for an experienced engineer who is passionate about protecting user data while enabling innovation. What You’ll Do Design, build, and operate backend services that enforce policy-driven data access, lifecycle controls, and privacy protections. Develop distributed authorization and identity-aware enforcement mechanisms integrated directly into data services and control planes. Implement auditability, policy hooks, and enforcement observability to ensure compliance is continuously verifiable. Partner with Security, Legal, and Compliance to convert privacy requirements into scalable technical designs and developer-friendly APIs. Harden data platforms and backend services through schema-level controls and data handling constraints by default. Collaborate with infrastructure teams to ensure consistent enforcement across systems while minimizing duplicated implementations. Contribute patterns, libraries, and education that elevate trustworthy data access patterns across the organization. You Might Thrive in This Role If You Have 5+ years of industry experience building and operating backend or infrastructure systems in production. Strong software engineering fundamentals , with fluency in at least one major programming language (e.g., Python, Go, Rust, C++, Java). Experience with distributed authorization, RBAC/ACL systems, encryption-based access, or policy engines. Familiarity with global privacy regulations and their architectural implications. Ability to influence and collaborate with teams across legal, compliance, product, and engineering. A bias toward practical, impactful solutions that balance privacy protections with product needs. Nice to Have Experience wi

About the Team The Preparedness team is an important part of the Safety Systems org at OpenAI, and is guided by OpenAI’s Preparedness Framework . Frontier AI models have the potential to benefit all of humanity, but also pose increasingly severe risks. To ensure that AI promotes positive change, the Preparedness team helps us prepare for the development of increasingly capable frontier AI models. This team is tasked with identifying, tracking, and preparing for catastrophic risks related to frontier AI models. The mission of the Preparedness team is to: Closely monitor and predict the evolving capabilities of frontier AI systems, with an eye towards misuse risks whose impact could be catastrophic to our society Ensure we have concrete procedures, infrastructure and partnerships to mitigate these risks and to safely handle the development of powerful AI systems Preparedness tightly connects capability assessment, evaluations, and internal red teaming, and mitigations for frontier models, as well as overall coordination on AGI preparedness. This is fast paced, exciting work that has far reaching importance for the company and for society. About the Role We’re hiring a Data Scientist to help build, evaluate, and continuously improve mitigations that prevent extreme harms from AI systems. This role is for an experienced, highly autonomous individual contributor who can take ambiguous problem statements, structure rigorous analyses, and translate findings into actionable product and policy changes. This position goes beyond “running evals.” You’ll help create mitigation intelligence and monitoring systems that enable OpenAI to detect issues early, measure effectiveness over time, and reduce both over-blocking (unnecessary friction) and under-blocking (missed harm). What You’ll Do Evaluate and improve mitigation systems, including classifiers and detection pipelines across domains (e.g., biosecurity, cybersecurity, and emerging risk areas). Diagnose false positives and fa

About the Role The Engineering Acceleration Delivery / Continuous Deployment team builds and operates the systems that safely ship OpenAI’s infrastructure and product code to production. We own the deployment platform, release pipelines, and rollout safety mechanisms that allow engineers across OpenAI to deploy changes rapidly while minimizing operational risk. Our mission is to make production deployments fast, safe, and increasingly autonomous. This role sits at the intersection of developer productivity, distributed systems reliability, and large-scale infrastructure orchestration. In This Role, You Will Design and build continuous deployment infrastructure that safely rolls out changes across dozens of Kubernetes clusters and global regions. Develop systems for progressive delivery, including canary releases, staged rollouts, and automated rollback. Improve engineering velocity by reducing friction in the release pipeline and automating manual operational workflows. Work with product and infrastructure teams to ensure their services are deployable, observable, and resilient at scale. Implement and evolve deployment methodologies such as GitOps, infrastructure-as-code, and progressive delivery patterns. Build systems that automatically evaluate deployment health using metrics, logs, traces, and alerts to detect regressions and trigger safe rollbacks. Build systems that support agent-assisted or autonomous deployment workflows using modern AI tooling. Technologies commonly used in this environment include: Kubernetes for large-scale container orchestration and runtime infrastructure Python and FastAPI for internal services Terraform for infrastructure as code GitOps-based deployment workflows (e.g., ArgoCD, Flux, or similar systems) Buildkite for CI orchestration You may be a strong fit if you: Have worked with Kubernetes-based deployment systems at scale Have experience building or operating continuous deployment platforms Are familiar with GitOps tooling such as

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Senior Software Engineer — Cortex Training The Snowflake ML Platform team's mission is to let customers run their most demanding ML/AI workloads inside Snowflake. Cortex Training is our LLM post-training platform: it turns scarce, expensive GPU capacity into a simple, composable service, so customers can adapt open-weight foundation models to their own business problems while we handle the hard distributed-systems parts, including scheduling, orchestration, multi-node training and inference, fault tolerance, and throughput. The platform already runs post-training at scale. Under the hood, it decouples GPU computation from the training loop and exposes it as primitive APIs that compose into everything from SFT to full RL workflows. You'll work alongside a team that ships fast & sweats reliability and the researchers behind DeepSpeed. We're looking for an engineer who thrives in the ML infrastructure layer and brings a solid understanding of LLMs and post-training to help us scale and grow it. YOU WILL: Design and build across the full stack — from the public training APIs and SDK through the control plane to the GPU data plane. Scale the distributed systems that make GPU compute serverless — multi-tenant scheduling, placement, and capacity-aware routing across regional G