Ai Support Engineer in United States

Why join us Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. Product at Brex The Product team is at the forefront of Brex's mission to empower employees anywhere to make better financial decisions. With a deep understanding of the business, we identify and scope out the most impactful opportunities for Brex to tackle. We are responsible for aligning cross-functional teams — such as Engineering, Legal, Compliance, and Design — on key decisions. We set strategy and drive products from inception to launch, enabling Brex to grow rapidly and help our customers reach their full potential. What you’ll do As a Product Leader at Brex, you will be the driving force behind our Growth Product team — overseeing the thoughtful strategy and execution of team and technical systems to drive customer acquisition and onboarding. You will also collaborate closely with our Go-to-Market (GTM) teams to ensure seamless acquisition and onboarding for customers, particularly those with significant and complex spending n

About the Team OpenAI's Legal team plays a crucial role in furthering OpenAI's mission by tackling innovative, fundamental legal issues in AI. If you're passionate about doing significant and unique work as a technology lawyer, this team is for you. The team comprises professionals from diverse fields, including technology, AI, privacy, IP, corporate, employment, tax law, regulatory, and litigation. About the Role As a member of our AI Product Counsel team, you will lead legal compliance initiatives for global online safety, platform, and AI regulations, including the UK Online Safety Act, EU Digital Services Act, EU AI Act, and similar emerging frameworks. You will partner closely with Product, Policy, Safety, Engineering, Security, Operations, and other teams to translate complex regulatory requirements into scalable, practical compliance solutions. 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: Serve as the primary legal expert on the Online Safety Act, Digital Services Act, EU AI Act, and related global AI, platform, and online safety regulations. Lead the design and implementation of scalable compliance programs, governance frameworks, controls, and operating processes. Partner with Product, Engineering, Safety, Policy, Operations, and Security teams to translate regulatory obligations into practical product and operational requirements. Monitor emerging regulations and enforcement trends, anticipate their impact, and help shape OpenAI’s compliance strategy. Develop repeatable processes, playbooks, escalation paths, and decision frameworks that enable teams to move quickly while managing risk responsibly. Support engagement with regulators, external counsel, industry groups, and other stakeholders as needed. You’ll thrive in this role if you: Have 10+ years of experience with a mix of in-house or technology-focused law firm roles. Have

About the Team OpenAI Finance ensures the organization is positioned for long-term success as we pursue our mission. The Order to Cash (OTC) team oversees the complete flow of commercial transactions from order intake and provisioning through billing, collections, and cash application — ensuring accuracy, compliance, and operational excellence in support of OpenAI’s mission to ensure artificial general intelligence benefits all of humanity. About the Role We are seeking a Senior Manager to build and scale Order to Cash across OpenAI’s API and ChatGPT businesses, cloud marketplaces, and strategic partnership channels. This role will own end-to-end Order Management and Billing operations across API and ChatGPT while leading OTC readiness and execution for AWS Marketplace, Google Cloud Marketplace, Oracle Cloud Marketplace, GovCloud, and future partner channels. The role will also own the end-to-end Order Management and Billing close, setting the close calendar, readiness standards, review and sign-off expectations, while leading the team responsible for execution. You will oversee the Order Management and Billing lifecycle across API, ChatGPT, marketplace, and partner transactions, spanning commercial readiness, order intake, provisioning, usage and transaction data, pricing validation, invoicing, credits, settlements, and product and partner reporting. Your work will ensure transactions are accurate, timely, complete, and supported by audit-ready controls. This is a leadership role that combines strategic ownership, cross-functional leadership, and hands-on operational execution. You will define the target operating model, lead first-of-kind launches, shape product and systems roadmaps, and oversee the resolution of complex contract modifications, non-standard pricing, usage disputes, reconciliation breaks, settlement variances, and customer- or partner-impacting escalations. You will collaborate with teams across Finance, GTM, Product, Engineering, Legal, Tax, Reven

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! About the Role Cohere is seeking a Global Public Policy Manager to lead policy engagement on compute infrastructure, export controls, AI competitiveness, and sovereign AI strategies. Governments increasingly view AI as critical national infrastructure and are investing heavily in compute capacity, energy resources, and domestic AI ecosystems. This role will help position Cohere as a trusted partner in emerging discussions around AI infrastructure, national competitiveness, and sovereign AI deployment. Key Responsibilities Monitor and analyze developments related to AI infrastructure, data centers, energy policy, semiconductor policy, export controls, and national AI strategies. Develop policy positions on sovereign AI, compute access, digital sovereignty, and AI competitiveness. Support engagement with governments developing AI infrastructure investment programs and national AI initiatives. Collaborate with commercial, product, and corporate development teams on strategic opportunities involving public-private partnerships. Represent Cohere in policy discussions related to AI infrastructure, energy requirements, and technology c

Datadog AI Research — Scholars Program with Carnegie Mellon University Datadog AI Research (DAIR) is partnering with Carnegie Mellon University to support a small number of PhD students working on open research problems grounded by ongoing efforts at Datadog/DAIR. You will frame a problem, run your own experiments, and write up what you find, with compute and data at a scale most academic labs cannot provide. You will collaborate with colleagues working on the same questions. The Lab And The Research: DAIR is an industrial research lab motivated by practical challenges in observability and software operation: detecting and diagnosing failures, understanding complex production environments, and helping engineers operate software more effectively. The lab focuses on creating specialized foundation models, post-training and evaluating AI agents, and building frontier-scale machine learning systems. By combining fundamental research with Datadog's large-scale, real-world data and infrastructure, the lab develops new AI capabilities and translates them into practical systems with meaningful impact. Internship projects are shaped with your DAIR mentor and your CMU faculty advisor. You do not need prior experience with observability, monitoring, or infrastructure. What You'll Do: Own a research project end to end: framing the question, running the experiments, writing it up Work directly with a DAIR mentor engaged in the same problem, and stay connected to your advisor and lab Publish, and use the work toward your dissertation See research reach production, when it works Who You Are: Currently enrolled in a PhD program at Carnegie Mellon in machine learning, computer science, statistics, or a related field Depth in at least one area relevant to the research above Comfort running real experiments — training models, working with GPUs, reading and reimplementing recent papers Evidence you can do research: conference or workshop papers, preprin

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 Team Pinterest's Ads Delivery Infrastructure team builds and operates the real-time serving, indexing, retrieval, and budgeting systems that power Shopping and Ads at Pinterest. We're in the middle of a significant modernization effort: unifying our catalog and index platforms to scale to billions of items, moving core services onto our next-generation compute platform, and re-architecting our budgeting systems for real-time accuracy. We work closely with engineering, product, and monetization teams to keep Pinterest's advertising systems fast, reliable, and ready to scale. What You'll Do: Lead or support programs that scale Pinterest's Shopping and Ads catalog, indexing, and retrieval systems to handle billions of items, partnering with engineering leads across catalog, search infrastructure, and retrieval. Drive cross-team execution on inf

Who Are We? Postman is the world’s leading API platform, used by more than 45 million+ developers and 500,000 organizations, including 98% of the Fortune 500. Postman is helping developers and professionals across the globe build the API-first world by simplifying each step of the API lifecycle and streamlining collaboration—enabling users to create better APIs, faster. The company is headquartered in San Francisco and has offices in Boston, New York, Austin, Tokyo, London, and Bangalore - where Postman was founded. Postman is privately held, with funding from Battery Ventures, BOND, Coatue, CRV, Insight Partners, and Nexus Venture Partners. Learn more at postman.com or connect with Postman on X via @getpostman. P.S: We highly recommend reading The "API-First World" graphic novel to understand the bigger picture and our vision at Postman. The Opportunity Postman is a rapidly growing Series D funded startup that specializes in providing innovative developer products and solutions for both individual developers and large enterprises. Our mission is to empower developers and organizations to create, test, and manage APIs more efficiently. We are currently seeking an experienced and highly skilled Field CTO to join our team, reporting to the CTO. In this role, you will work closely with customers to understand and guide their API strategy, ensuring Postman's products and services are seamlessly integrated into their architecture. What You’ll Do Act as a trusted technical advisor to Postman customers, helping them understand and navigate their API strategies and identify opportunities for Postman's products and services to add value. Collaborate with the sales and customer success teams to provide technical guidance during the pre-sales, onboarding, and ongoing support processes. Develop and deliver customer-facing presentations, demos, and workshops to demonstrate the value of Postman's solutions and help customers optimize their API management processes. Gather custome

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 strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you'll be working on Modal's machines layer: the fleet of bare metal and cloud hosts that every Function, Sandbox, and training job runs on, and the control plane that provisions, images, monitors, and repairs them. You'll automate the integration of new capacity from a growing set of hardware providers; from auditing and benchmarking hosts and clusters, to maintaining our machine images, configuring GPUs, RDMA, networking, and storage, and getting machines into production. You'll build the automation that keeps the fleet healthy without human intervention: detecting bad GPUs, thermals, and disks. You'll dig into whatever is between the hardware and the software that runs on

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 strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you'll be working on the distributed object storage system that underpins every container image, volume, and checkpoint on Modal: hundreds of petabytes of data, replicated across multiple cloud object stores and a CDN, cached on local NVMe across a large fleet of workers in many datacenters, and shared peer-to-peer within each datacenter. You'll make cold starts feel local when the data is hundreds of milliseconds away, designing the caching, preloading, and peer-to-peer layers that hide object-store latency and keep public ingress off saturated uplinks. You'll own durability and cost at petabyte scale, from streaming and batch replication between origins, to garbage collecti

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 a strong technical lead to guide the engineers designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. You'll lead the team responsible for Modal's machines layer: the fleet of bare metal and cloud hosts that every Function, Sandbox, and training job runs on, and the control plane that provisions, images, monitors, and repairs them. You'll own the full lifecycle of a machine, from accepting and benchmarking new hardware from a growing set of providers, to network bring-up, kernel and image management, GPU and disk health tracking, and automated remediation of unhealthy hosts. You'll manage a team of 3–8 engineers while staying hands-on across the stack which involves BMCs, firmware, PXE, bootloaders, Linux networking, drivers, and distributed control-plane services, and you'll shape our long-

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 a strong technical lead to guide the engineers designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. You'll lead the team responsible for the distributed object storage system that underpins every container image, volume, and checkpoint on Modal: hundreds of petabytes of data, replicated across multiple cloud object stores and a CDN, cached on local NVMe across a large fleet of workers in many datacenters, and shared peer-to-peer within each datacenter. You'll set technical direction for the primitives that other teams (filesystems, training, sandboxes) build on, balancing durability, latency, throughput, and cost. You'll own the roadmap from today's hardest problems (garbage collection at petabyte scale, active-active replication, rate limiting that protects the upstream without wasting ut

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. The role... Synthesia's API and platform capabilities are quickly becoming the way developers embed AI video into their own products — automated training pipelines, localization workflows, customer-facing apps, and more. We're looking for our first Developer Advocate to make sure the developer world knows it, understands it, and gets building. This is a builder-and-storyteller role. You'll be the face and voice of the Synthesia API to the outside world — writing, coding, speaking, and showing up wherever developers already are — while also being the internal champion who brings their feedback back into the product. You won't just talk about what's possible with Synthesia; you'll build the sample apps, tutorials, and demos that prove it, and you'll do it consistently enough that developers start to recognize your name before they recognize the logo. You'll be part of the Developer Services team and work closely with Product, Engineering, Marketing, and Developer Support to turn technical capability into developer adoption. What You'll Do Create technical content that developers actually use Write blog posts, tutorials, and how-to guides that show real, working integrations — not just feature announcements Build a

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 strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Requirements: 5+ years of experience writing high-quality production code Experience building high-performance distributed systems at a large scale (the more battle scars, the better) Strong cloud skills Strong knowledge of low-level operating system foundations (Linux kernel, file systems, containers, etc.) Experience with performance engineering (tell us a story of when you shaved off a few milliseconds!) Ability to work in-person in our NYC or SF office. Prior experience with Rust is nice to have, but not required. Ability to participate in on-call rotation and respond to production incidents.

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 strong engineers with experience in making ML systems performant at scale. If you are interested in contributing to open-source projects and Modal’s container runtime to push language and diffusion models towards higher throughput and lower latency, we’d love to hear from you! Requirements: 5+ years of experience writing high-quality, high-performance code. Experience working with torch, high-level ML frameworks, and inference engines (vLLM or TensorRT). Familiarity with Nvidia GPU architecture and CUDA. Experience with ML performance engineering (tell us a story about boosting GPU performance — debugging SM occupancy issues, rewriting an algorithm to be compute-bound, eliminating host overhead, etc). Nice-to-have: familiarity with low-level operating system foundations (Linux kernel, file systems, containers, etc).

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 strong backend engineers who love building a developer tools used by the largest AI companies in the world. You’ll be building for things at scale, but also for new AI workflows that change every day. Requirements: Experience building and shipping modern web applications end-to-end. We care more about what you’ve built than how many years you’ve been building. Comfort working across the stack: TypeScript on the frontend, Python services on the backend, and ClickHouse for data and analytics. Deep knowledge of observability tools and patterns used for large-scale workloads such as custom sandboxes, training and inference for large language (LLM) and diffusion models. Experience with at least one of: billing/payments systems, B2B SaaS tooling, or enterprise software, or LLM / diffusion models inference and training loads. Strong product instincts; yo