Ai And Cloud Service Provider Account Executive in United States

About the Team OpenAI develops models that can reason through complex problems and hardware designed for the demands of advanced AI. AI for Chips connects these efforts: applying increasingly capable AI systems to the work of semiconductor engineering. Our goal is to help engineers develop better chips and shorten design cycles. This work brings research, model training, and hardware expertise together to build tools that engineers can use on real designs, with correctness and measurable performance at the center. About the Role We’re hiring a Software Engineer to build the research infrastructure and tooling that help OpenAI models design silicon. You’ll turn chip-design workflows into reliable environments for reinforcement learning and evaluation, and make it easier for researchers to run experiments and iterate on new ideas. You’ll move between software engineering, tool integration, and open research problems. We value strong coding fundamentals, clear technical judgment, and independent execution. Prior chip-design experience is helpful, but you can learn the domain alongside the team’s hardware specialists. In this role, you will: Build and maintain infrastructure for reinforcement learning environments, evaluations, and long-running experiments. Integrate electronic design automation (EDA) tools into workflows for RTL generation, verification, and physical design optimization. Improve experiment reliability, reproducibility, observability, and performance; debug failures across tools, services, and infrastructure. Develop tooling and model harnesses that let researchers test ideas quickly and measure correctness and power, performance, and area (PPA). Collaborate with researchers and engineers to turn successful experiments into reusable systems and training workflows. Own ambiguous projects end to end, communicate progress, and use results to guide the next iteration. You might thrive in this role if you: Have strong software engineering fundamentals, with

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. At Snowflake, we empower both enterprises and individuals to reach their full potential. Our culture prioritizes impact, innovation, and collaboration, making Snowflake the ideal place to build ambitious projects, execute quickly, and advance technology — and your career — to the next level. The Role We are seeking a Senior Manager, Applied Field Engineering — AI/ML Product Specialists to lead a high-performing team of AI/ML specialists at the intersection of product, field, and customer success. In this hands-on leadership role, you will manage a team of Applied Field Engineers who are deep practitioners in Snowflake's AI/ML product portfolio — including Cortex AI, ML modeling, and agentic workflows. You will drive product adoption and customer outcomes, ensuring customers move beyond initial activation to unlock the full depth of Snowflake's AI/ML capabilities. Critically, you will serve as a strategic bridge between the field and Snowflake's product organization — translating customer experience into structured product insight that directly shapes roadmap priorities. You will work closely with Product Management, Engineering, and Sales leadership to ensure Snowflake builds the right things and customers realize their full potential. Responsibilities & Focus Areas Pro

What we're building Mutiny is the self-improving AI infrastructure for GTM teams to execute faster and close more revenue. Our ambition is to do for revenue velocity what Cursor and Claude Code did for engineering velocity. With Mutiny, everyone in sales and marketing gets a bench of GTM athletes that handle any work across their revenue motion and learn from what's actually moved their deals. In April we re-launched the product as an agent-first platform. Anthropic showcased us as a leader in AI GTM. MRR is growing more than 70% month-over-month, with customers like Uber, Rippling, and Snowflake. We're backed by Sequoia, YC, and Insight, and we're building a generational company. The opportunity Most engineers spend their career making predictable systems faster. You'll spend yours making non-deterministic ones trustworthy. As a senior engineer on our AI product team, you'll architect the Campaign Builder and Agent experiences marketers and sellers open every day to go from idea to personalized assets in minutes. You'll partner directly with product, design, and the founders to define what an agent-first GTM platform should feel like, and your calls on architecture, evals, and guardrails compound across thousands of customer accounts. This role is in person in New York City, five days a week, and we ship weekly. What you'll own The core agent surfaces. Architect and ship the Campaign Builder and Agent experiences end-to-end. Frontend, backend, prompts, evals, the whole stack. Reliability on top of LLMs. Make non-deterministic models feel deterministic at the surface. Build the retries, fallbacks, and orchestration so the customer never sees the failure mode. Evals and guardrails. Define how we measure quality, catch regressions, and keep brand and tone consistent across thousands of customer accounts. Speed and feel. AI products live or die by latency and the loop between intent and output. You'll obsess over both, and use coding agents and agent networks to ship f

What we're building Mutiny is the self-improving AI infrastructure for GTM teams to execute faster and close more revenue. Our ambition is to do for revenue velocity what Cursor and Claude Code did for engineering velocity. With Mutiny, everyone in sales and marketing gets a bench of GTM athletes that handle any work across their revenue motion and learn from what's actually moved their deals. In April we re-launched the product as an agent-first platform. Anthropic showcased us as a leader in AI GTM. MRR is growing more than 70% month-over-month, with customers like Uber, Rippling, and Snowflake. We're backed by Sequoia, YC, and Insight, and we're building a generational company. The opportunity Most post-sales leaders inherit a process. You'll build it. As our AI strategist lead, you'll own Mutiny's managed account book and lead the technical solutions function that backs up our most complex customers. The teams running Mutiny (Rippling, Uber, Snowflake, Zendesk, and Gusto) are betting hard on AI, and they need post-sales partners who move their roadmap forward, not just their renewal date. You'll set the bar for what great support looks like, build the playbooks that let CS scale, and step into people management as we hire AI strategists underneath you. This role is in person in New York City. The teams running Mutiny (Rippling, Uber, Snowflake, Zendesk, and Gusto) are betting hard on AI, and they need post-sales partners who move their roadmap forward, not just their renewal date. They don't need a partner who tracks their renewal date; they need one who moves their roadmap forward and shows them what's possible with the product before they ask. You'll set the bar for what great looks like, build the playbooks that let CS scale, and grow into people management as we hire AI Strategists underneath you. This role is in person in New York City. What you'll own The managed book. Onboarding, adoption, retention, and expansion across every managed account at Mutiny. T

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. 🚀 Role Overview You'll own and evolve the AI systems behind ClickUp's voice platform: real-time streaming transcription, intelligent reformatting, context-aware mention detection, and voice-to-action pipelines. This is a high-impact, hands-on role where you'll push the boundaries of what voice interfaces can do inside a productivity tool used by millions. Key Responsibilities Design, build, and optimize real-time speech-to-text pipelines (streaming ASR, VAD, audio processing) Improve transcription accuracy through context injection (user names, teams, custom vocabulary, language detection) Develop and maintain LLM-powered post-processing (grammar correction, filler removal, mention resolution, formatting) Build voice-to-action systems that parse natural language into structured workspace commands Evaluate, benchmark, and integrate ASR models (Whisper, AssemblyAI, Fireworks, etc.) for cost, latency, and accuracy Collaborate with product and platform teams to ship voice features across MAX Desktop, Mobile, Web, and Browser Extension Explore multimodal AI capabilities (screen + voice + text) for next-gen assistant experiences Equal Opportunity Employer ClickUp is an Equal Opportunity Employer, and qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin. Privacy Notice ClickUp collects and processes personal data in accordance with applicable data protection laws. You can find further details by viewing our Global Candidate Privacy Notice. If you are a Philippine Job Applicant, please also see our Phi

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 The Financial Intelligence team, part of Ramp's Applied AI org, powers the agentic analysis, FP&A, and book-close experiences that over 70,000 businesses rely on to run their finances. We turn messy financial data into a fast, trustworthy, governed data layer that AI agents can work with and build artifacts on top of. This is a frontend-leaning role for an engineer who obsesses over interaction design and data-dense UX, but is just as comfortable designing the API that feeds it. You'll own the surfaces customers actually touch: agentic financial analysis, month-end close, and exploratory data experiences that feel as polished as the best business intelligence tools. If you want your frontend work to sit at the center of real production LLM systems rather than being bolted on at the end, this is the role. What You’ll Do Design and ship customer-facing AI experiences end to end, from React UI through to the APIs and data contracts behind them Build BI-tool-quality interfaces for agentic analysis, FP&A, and book-close workflows:

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. At Ema, we build AI Employees that operate inside the enterprise. Healthcare is where the bar is highest: the output has to be accurate, auditable, and clinically sound. We're opening a part-time role focused on agent measurement and improvement. You'll instrument how our healthcare AI Employees perform in production, identify where quality breaks down, and design the experiments that close the gap — partnering with clinical experts to ensure improvements translate into better patient outcomes, not just better metrics. We're looking for strong analytical judgment (Python, agent lead development), comfort operating with incomplete information, and genuine interest in the healthcare domain. Clinical experience is valued but not required. This engagement is structured as a paid internship or contract engagement, with weekly syncs in our Bay Area office. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits. Ema Unlimited is an equal opportunity employer and is committed to providing equal employment opportunities to all employees and applic

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As an Senior AI Engineer at GitLab, you'll help build the foundation for GitLab's transformation into an AI-first company. Reporting to the Director, Enterprise AI, you'll be a hands-on technical leader responsible for delivering internal AI-powered solutions that drive measurable business outcomes. Building fast matters, but it's not enough on its own. This role starts with understanding the real problem: mapping how work moves across teams, tools, and handoffs, identifying the true constraint, and validating whether AI is the right solution before you begin development. From there, you'll take ownership

About the Team The Codex Core Agent team builds the kernel of Codex. We own making the agent better, accelerating research, and making those improvements real in production for our users. That means working across the systems that make Codex actually function as an agent in the real world: the production performance envelope around tokens, latency, reliability, cost, and capacity; the core execution loop and interfaces that turn models into useful behavior; the shared infrastructure that enables other teams to build on Codex; and the feedback loops that turn real-world usage into better models and better agent behavior over time. About the Role We’re looking for applied AI engineers to help bring Codex agents from impressive demos to dependable tools. This role is about improving agent performance on real software engineering tasks and closing the gap between research capability and real-world usefulness. You’ll work closely with research, infrastructure, and product to ensure agents are not just powerful, but useful, steerable, and reliable in practice. The job is not only to improve model behavior in isolation, but to turn those improvements into measurable gains in solve rate, usefulness, and economic value for users. What You’ll Do Design and iterate on agent behaviors across real-world coding tasks and long-horizon workflows. Work closely with research to develop and run evals to measure agent performance, regressions, failure modes, and edge cases. Improve performance through prompting, tool-use strategies, context construction, and model-facing experimentation. Analyze failures in production and systematically improve robustness and reliability. Build feedback loops and data systems that get better real-task data into evaluation and research. Work with product teams to shape user-facing agent experiences and the interfaces the agent depends on. Help define what “good” looks like for agents completing complex tasks end-to-end. You Might Be a Good Fit If You Ha

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. The residency You own one hard problem end to end. You write the proposal, build the system, design the evaluation, ship behind a gate, and finish with a write-up of what turned out to be true, including the parts that didn't work. You'll sit in the production codebase with a senior mentor and real production data. Recent residents have shipped self-improving harnesses, inference-cost work, agent memory, and eval infrastructure. Your project gets scoped with you, not handed to you. The problem space The loop we care about: production traces become data, data becomes training and evaluation, and better agents produce better traces. Projects live somewhere on that loop. Harness and inference-time work. Context engineering, tool and skill design, orchestration, and deciding where extra inference compute actually pays. Self-improvement loops run behind hard fences. Post-training for agents. SFT on curated trajectories, preference optimization, RL on real agent tasks. Reward design where outcomes are verifiable, process vs. outcome supervision, distilling frontier behavior into cheaper models. Environments and rewards. Turning enterprise workflows into training and eval environments: fi

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. Snowflake is about empowering enterprises to achieve their full potential — and people too. With a culture that’s all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology — and careers — to the next level. ABOUT THE ROLE: You will work on critical business initiatives in the core database engine, bring an AI-forward approach to software development and accelerate roadmap cycles for the benefit of our customers. Your work will directly impact how developers and businesses build with data. You'll own the full AI engineering lifecycle: design, prompt/tool engineering, evals, deployment, measurement, and optimization. You'll work with a small, high-powered engineering team. What you will do in this role: Own features end-to-end for Snowflake Database Engineering products. Build agentic workflows, coding harnesses, evaluation pipelines. Build enterprise-grade context engineering: function calling, tool schemas, guardrails, agent teams, and verification/repair. Design evals and hillclimb : create golden sets, create rubrics and metrics, analyze errors, run experiments to hill climb on the metrics. Partner with product and infra: translate customer problems into products and experiments. Collaborate with infr

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. We are hiring a Staff Research Scientist, Physical AI for our AI Research team . You will build the next-generation training and learning platform for physical AI: models that perceive, reason about, and act within structured environments . This is a greenfield (0 to 1) effort at the intersection of representation learning, world models, and policy optimization. You will help define its technical direction from day one. AS A STAFF RESEARCH SCIENTIST YOU WILL: Design and build scalable training infrastructure for representation models (e.g., contrastive and self-supervised approaches like CLIP/SigLIP, DINO/MAE, and joint-embedding predictive architectures) Develop latent world models that learn environment dynamics through imagined rollouts, enabling model-based reasoning and planning (Dreamer-style, I-JEPA/V-JEPA families) Architect and implement action/policy model pipelines, including vision-language-action models and diffusion-based policy learning Build generative simulator frameworks that produce controllable, physically plausible future states (video world models in the spirit of Cosmos/Genie/Sora) Develop multimodal generative model capabilities that fuse visual, language, and structured inputs for downstream reasoning and decision-making Lead cross-team technical de

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. THE MISSION We are seeking a Staff Research Scientist to serve as a technical pillar within our AI research organization. You will not just execute on roadmaps—you will define them. At the intersection of autonomous agents and large language models (LLMs) , you will build the models and systems that turn enterprise data into self-directed, decision-making agents —shifting from passive data access to autonomous execution. Our team operates at the frontier of enterprise AI, delivering both state-of-the-art models and production systems , including: Arctic LLM : Enterprise foundation models optimized for performance and efficiency Arctic-Text2SQL : Post-trained reasoning models with frontier-level quality at a fraction of cost and latency Snowflake Intelligence : Brought research to production through agentic innovations in multi-step reasoning, Deep Research for structured and unstructured insights, and system optimization Arctic Inference : High-performance LLM serving stack (Shift Parallelism, SwiftKV), open-sourced and powering Snowflake Cortex Arctic Long-Context Training : Enables 1M+ token context training on a single H200 GPU Agent World Models (AWM) : RL training across 1,000+ synthetic environments for tool-using agents We focus on core challenges such as reliable re

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. At Snowflake, we are building a high-impact team to help the world's most innovative companies unlock the power of AI. As a Senior Forward Deployed Engineer, Applied AI on our Cortex AI team, you will be a hands-on technical leader and trusted partner to our most strategic customers. You will own the end-to-end delivery of enterprise AI programs, leading a team of 2–4 engineers while staying deeply technical yourself. You will set the technical direction for your customer engagements, mentor your team, and serve as the senior technical voice at the intersection of product, engineering, and customer success. IN THIS ROLE AT SNOWFLAKE, YOU WILL: Lead Customer Programs : Own the full lifecycle of complex, multi-engineer AI engagements – from scoping and architecture through deployment, monitoring, and handoff. Be accountable for delivery quality and customer outcomes for the projects you lead. Own AI Quality : Define what "good" means for each engagement. Translate ambiguous customer goals into measurable quality metrics, evaluation frameworks, and golden datasets – then run systematic eval loops to hill-climb on agent quality, catch regressions before customers do, and continuously raise the bar on accuracy, faithfulness, and safety. Set the standard for how the team measures

Become a part of our caring community *(Selected candidate will be required to live within 60 mins of one of the following metro locations OR be willing to relocate to within 12 months of hire date: Louisville KY, NYC Metro, Dallas Metro, Charlotte NC Metro, Tampa, Miami, Washington DC metro, Chicago, Boston, Atlanta, Nashville) The Senior Security Architect for AI works with EIP Department leaders and Humana enterprise stakeholders to identify, define, and develop security architecture requirements and secure designs for AI technology solutions across Humana's business, information technology, and security domains. The Security Architect leads the development of technical architecture & designs, develop security requirements, perform threat modeling and ensures alignment of security & risk imperatives with business priorities. The Security Architect is responsible for the high-level design and patterns of security program infrastructures to enable the protection of Humana tools, data, systems, and networks. Working with EIP Leaders, the security architect drives alignment between the EIP security strategy, security architecture and infrastructure, and Humana's overall business and technology strategic priorities. In this capacity, the role is responsible for planning, designing, and proposing architectural patterns or security enhancements for Humana's information security and technology infrastructures. The role works with EIP and Humana leaders to review and reconcile Humana business priorities with EIP security requirements. The role engages with relevant EIP stakeholders to identify current and emerging security threats and works to design security architecture elements to mitigate threats as they emerge. Additionally, the role actively works to identify gaps within existing EIP reference architecture and designs updates to impacted sec