Ai Hpc Neocloud Pre Sales System Engineer Uae in United States

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 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 a Growth Engineer to own the technical foundation of Modal's marketing and developer-facing web surfaces: the marketing site, docs site, growth landing pages, high-profile microsites, forms, analytics instrumentation, and the integrations that help users discover, understand, and get started with Modal. This is a frontend-heavy role for someone with strong product taste, web engineering craft, and a business-owner mindset. You'll partner with Product Engineering, Design, Data, and Growth to ship polished, measurable web experiences from high-profile projects like the GPU Glossary and LLM Engine Advisor to internal tooling that helps teams publish content faster. When this role is going well, Modal launches new pages, docs experiences, campaigns, and experiments quickly without sacrificing performance, craft, or measurement. In this role you will:

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: Most of the value of owning a model shows up at serving time. We're building a platform that covers the whole life of an LLM -- train it, deploy it, observe it -- and inference is where teams feel the difference every day. We already run elastic inference, sandboxes, distributed volumes, and multi-node training, and we control the infrastructure underneath, so the serving stack is ours to shape rather than something we resell. You will do hands-on inference research at Modal, working with the research lead to pick high-impact bets and owning them end to end. The bets that matter most are the ones that move cost per token and tail latency on the workloads our customers actually run. What you'll do: Own end-to-end inference research bets: speculative decoding, disaggregated prefill/decode, quantization (FP8, INT4), KV-cache and memory management, autoscaling for spik

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 a Detection & Response Engineer to build the systems that help us identify, investigate, and respond to threats across our platform. This is an engineering role focused on automation. You'll build detections, investigation tooling, and response capabilities that scale with our infrastructure, using AI where it meaningfully improves signal, investigation speed, and operational effectiveness. You'll work closely with infrastructure, platform, and security engineers to ensure every incident makes the platform more resilient. What You'll Work On: Detection Engineering Design and build high-fidelity detections for attacks, abuse, and anomalous behavior across our infrastructure and production systems Continuously improve detections based on telemetry, threat intelligence, and lessons learned from incidents Improve visibility across cloud infrastruc

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 building a platform that covers the whole life of an LLM: training it, deploying it, and observing it in production. We already run multi-node training, elastic inference, sandboxes, and distributed volumes, and we control the infrastructure underneath. We’re looking for research depth in post-training to sit alongside our systems and product work. What you'll do: We are looking for research scientists with a strong track record in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. This role 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 robustnes

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. 🚀 Job Summary As a Business Systems Engineer on the GTM Engineering team, you will design, build, and operate the automation and AI systems that power ClickUp's Go-To-Market business — spanning core business products and the integration platforms that connect them. This role is AI-native at its core: you won't just maintain existing workflows, you'll actively advance our GTM systems with intelligent agents, LLM-powered automations, and next-generation integration patterns built on MCP, ClickUp Super Agents, and modern iPaaS tooling. You'll sit at the intersection of business systems architecture and applied AI — partnering with Sales, Finance, Revenue Operations, and fellow GTM Systems engineers to eliminate toil, accelerate revenue workflows, and build the automated, AI-augmented infrastructure the company runs on. This is a hands-on engineering role for someone deeply fluent in enterprise business systems, excited about deploying production AI, and committed to genuine ownership of the platforms they build — directly supporting GTMSOE's broader mission of operational excellence across the GTM org. Key Responsibilities AI-Native Automation & Agent Development Design and build AI-powered automations and agentic workflows across the GTM tech stack — including Salesforce, NetSuite, Workato, and MuleSoft — to eliminate manual effort and accelerate business operations. Develop and deploy ClickUp Super Agents and LLM-based automations to automate tasks such as deal data enrichment, quote generation assistance, order validation, revenue recognition triggers, and exception handling in quote-to-cash workflow

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. About the Role As the Product Manager for Tax, you will own the vision, strategy, and roadmap for Ramp’s next generation of AI-powered tax products. You will build solutions to automate tax calculation, validation, and filing for our existing suite of products (card, bill pay, banking, etc), for both domestic and international use cases. You’ll also be accountable for **expanding** Stack - our agentic accounting product - into the tax automation domain, to automate the work of CPAs. You’ll partner closely with engineering, design, data, and cross-functional stakeholders (Finance, Legal, Security, CX, Sales) to build intelligent experiences that help customers save money, reduce risk, and eliminate manual work. This role blends AI-native product development (LLM-powered workflows, evaluation systems, human-in-the-loop design) and deep domain expertise in domestic/international tax and CPA’s workflows. You will define and execute a strategy that will unlock new markets for Ramp and help us save our customers even more time and money. Please note that

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview Instacart's Fraud, Appeasement & Identity team protects the marketplace and everyone who depends on it: customers, shoppers, retailers, and brand partners. Within this team, the Identity Platform group builds and operates the core services that verify who our users are, secure their accounts, and provide trustworthy identity and eligibility signals to systems across Instacart. We're looking for an Engineering Manager to lead the Identity and Risk Platform team. In this role, you'll own a critical part of Instacart's trust infrastructure across authentication, account lifecycle, identity verification, and graph and relationship modeling, while managing and developing a team of backend and platform engineers. Your work will directly influence fraud losses, account security, marketplace integrity, and Instacart's ability to scale responsibly while meeting

About Flexport: At Flexport, we believe global trade can move the human race forward. That’s why it’s our mission to make global commerce so easy there will be more of it. We’re shaping the future of a $10T industry with solutions powered by innovative technology and exceptional people. Today, companies of all sizes—from emerging brands to Fortune 500s—use Flexport technology to move more than $19B of merchandise across 112 countries a year. The recent global supply chain crisis has put Flexport center stage as we continue to play a pivotal role in how goods move around the world. We are proud to have the support of the best investors in the game who believe in our mission, solutions and people. Ready to tackle global challenges that impact business, society, and the environment? Come join us. The Opportunity The Autonomous Freight Systems team is a brand new, AI-first engineering team in San Francisco, building Flexport's client-facing rates platform and self-serve freight booking experience from the ground up. We own two of the highest-leverage surfaces in the Client App: how clients see pricing and how they book freight without manual intervention. As a Senior Engineer, you will own significant technical domains end-to-end, not just features, but whole problem spaces. You will drive the engineering of systems that power rate visibility, pricing intelligence, and AI-assisted booking across ocean, air, and trucking. You don't wait to be told what to build next; you identify the highest-leverage problems, propose solutions, and see them through to production. You will be a technical force multiplier on the team: raising the bar on code quality, helping junior engineers grow, and shipping with a velocity and confidence that comes from deep ownership. This is a ground-floor opportunity to build the platform that moves Flexport from an assisted-sales model to a tech-run one for the long tail of our client base—turning the complexity of global trade into a s

Location Details: At GoDaddy the future of work looks different for each team. Some teams work in the office full-time, others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely. This is a remote position, so you’ll be working remotely from your home. You may occasionally visit a GoDaddy office to meet with your team for events or meetings. This position is not eligible to be performed in Alaska, Mississippi, North Dakota, or the Virgin Islands. GoDaddy is not currently considering candidates for this role in California, Seattle, or NYC. Join Our Team GoDaddy is hiring a Staff Software Engineer to help define and scale our Internal Developer Platform —a centralized system that powers how engineers across the company build, deploy, and operate software. This platform is used by 1,000+ engineers to manage everything from cloud infrastructure and application lifecycle to security, compliance, and cost transparency. In this role, you’ll operate as a technical leader at platform scale, shaping the architecture and direction of systems that directly impact engineering velocity across the company. You’ll work on high-impact initiatives such as AI-powered developer tooling, next-generation API platforms, and the evolution of a unified developer experience spanning APIs, CLI, and UI. This is a high-ownership, high-visibility role where Staff Engineers drive decisions, influence product direction, and partner across infrastructure, security, and platform teams. If you’re motivated by building systems that improve how other engineers work—and want to have a measurable impact on developer productivity at scale—this team sits at the center of GoDaddy’s engineering ecosystem. What You’ll Get to Do... Design and build platform services that power GoDaddy’s internal developer ecosystem, used by 1,000+ engineers. Lead architecture and technical direction for high-scale APIs, infrastructure orchestration,

Location Details: At GoDaddy the future of work looks different for each team. Some teams work in the office full-time, others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely. This is a remote position, so you’ll be working remotely from your home. You may occasionally visit a GoDaddy office to meet with your team for events or meetings. This position is not eligible to be performed in Alaska, Mississippi, North Dakota, or the Virgin Islands. GoDaddy is not currently considering candidates for this role in California, Seattle, or NYC. Join Our Team... We are seeking a highly skilled Senior Security Engineer to join our advanced Security Operations team. This role is focused on leading complex incident response and forensic investigations across Windows, macOS, Linux, and AWS environments while helping modernize security operations through automation and AI-driven capabilities. The ideal candidate is a hands-on security expert with deep AWS security expertise, strong threat detection and digital forensic skills, and experience leveraging AI and machine learning technologies to improve detection, response, and operational efficiency. You will play a key role in protecting critical assets, conducting high-impact investigations, mentoring team members, and driving the evolution of our security program against sophisticated and emerging threats. What You'll Get to Do... Lead high-priority incident response and forensic investigations, serving as the primary escalation point for advanced analysis, containment, recovery, root cause determination, and executive-level reporting. Drive threat detection and response across AWS, Windows, macOS, Linux, and endpoint security platforms, leveraging services such as GuardDuty, Security Hub, Detective, CloudTrail, IAM, VPC Flow Logs, and SentinelOne. Conduct malware analysis, host and cloud forensics, evidence collection, and threat hunting activi

The Company Delight.ai (formerly Sendbird) is on a mission to build the AI workforce of tomorrow. For over a decade, we built the infrastructure behind conversations—chat, voice, video, messaging APIs—and became the #1 CPaaS platform for in-app communications. 4,000+ brands trust us. 7 billion messages flow through our platform every month. 300 million monthly active users. We powered conversations for DoorDash, Match Group, Noom, Yahoo Sports, Rakuten, and thousands of others. We were good at what we did. Really good. We also saw it early: AI would fundamentally reshape how businesses talk to customers. The infrastructure we'd spent a decade building would become commoditized. The value would move up the stack—into intelligence, into experience, into outcomes. We had a choice: protect what we built, or reinvent ourselves. We chose reinvention. In December 2024, we made the full strategic pivot to AI-first customer experience. By February 2025, we'd launched our AI agent for enterprise CX—built on a decade of conversation data, now with intelligence on top. And in November 2025, we rebranded to Delight.ai. The name says it all. AI's real promise isn't efficiency or cost savings. It's giving customers back something they lost—the feeling of being truly understood and cared for. Not satisfied. Delighted. The Product Delight.ai is the AI concierge for customer experience. Most AI agents forget you the moment the conversation ends. Ours doesn't. Delight.ai builds memory over time, learns preferences, and connects context across every channel—chat, SMS, email, voice, WhatsApp—without losing the thread. We're building AI that makes customers feel understood, seen, and remembered. The Role We’re looking for a Sales Development Representative with drive, energy, and a capability for sparking conversations with prospects. You will play a critical role in our sales and marketing team by prospecting, discovering, and expanding business opportunities. You will identify the righ

Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey – from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk for one single system that is designed to meet the needs of modern day support teams. Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support. Driven by our core values, we push boundaries, build with speed and intensity, and relentlessly deliver incredible value to our customers. What's the opportunity? Are you ready to lead the charge in AI-driven customer service? As a Relationship Manager, you will be a key member of the team leading the growth & expansion of our business in Latin America. We’re building a world-class sales organization, and the road ahead is going to be very exciting. In this role, you'll be a key player in driving Intercom's growth and managing existing relationships within the LATAM region. You will possess both nurturing and hunter mindsets, proactively managing and owning LATAM's book of business to ensure client satisfaction and uncover expansion opportunities. What will I be doing? Develop and maintain strong relationships with existing clients, identifying opportunities for upselling and cross-selling Intercom's solutions. Provide timely and accurate forecasts and clear visibility on revenue performance Maintain up-to-date knowledge of our evolving products and processes Create your own demonstrations, tailored to client

About the Team The Early Access Program (EAP) team leads high-impact alpha programs at the intersection of customers, Product, Research, Engineering, GTM, Security, Legal, and launch teams. We partner with customers to test emerging capabilities with real-world use cases, surface actionable insights, and support launch decisions. Our team is made up of builders who learn quickly, collaborate deeply, create clarity in ambiguity, communicate openly, and iterate constantly. About the Role We’re hiring an Early Access Deployment Engineer to lead technical engagements with customers who are leveraging our frontier capabilities to solve real-world use cases. You will work at the earliest—and often messiest—stage of development, when capabilities are still unclear, tooling and processes are evolving, and the path from promising technology to a valuable real-world application has yet to be defined. You will be a hands-on builder, problem solver, and technical partner to customers and our research/product team. You’ll push beyond initial assumptions, identify high-value use cases, prototype solutions, design useful evaluations, and troubleshoot what is and is not working. Managing multiple customer engagements at once, you will help customers navigate ambiguity and difficult technical decisions while translating their experience into clear, actionable feedback for Research and Product. You will also own the end-to-end execution of early access programs—from onboarding customers, supporting live experimentation, synthesizing findings, and informing launch decisions. You’ll collaborate deeply with Research, Product, Engineering, Applied Evals, GTM, Legal, Security, Marketing, and other launch partners to create clarity, manage risk, and keep programs moving through changing conditions. Success in this role means turning frontier capabilities into real-world customer value and high-quality research signals. You will develop reusable technical approaches from early deployments,

About the Team OpenAI’s Forward Deployed Engineering (FDE) team turns research breakthroughs into production-grade systems. We embed deeply with customers to solve high-leverage problems and act as the delivery engine for our most complex large-scale engagements. We move quickly from prototype to production and surface reusable patterns that shape our platform. We operate at the intersection of deployment and development – working closely with OpenAI Research, Product and Partnerships. About the Role As a Technical Deployment Lead (TDL), you will define how OpenAI delivers complex systems to Semiconductor customers. You will own how solutions are scoped, built, shipped, and adopted across high-value engineering workflows such as RTL design, verification, and physical implementation. You’ll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will focus on the semiconductor vertical to deploy next-generation AI capabilities. You will own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You’ll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that shifts roadmaps/architectures). This is a high-trust, high-autonomy role. Success requires deep technical project m