Ai And Cloud Service Provider Account Executive in United States

About the Team Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role We are seeking a Mechanical Engineer to design, build, and own the mechanical side of our robotic actuator dynamometer and test infrastructure. You will create the test stands, couplings, fixtures, load paths, guarding, and serviceable lab hardware that enable rigorous characterization of robotic actuators. This role combines precision mechanical design with hands-on lab work. You will take robotic actuator test infrastructure from requirements and analysis through CAD, fabrication, assembly, commissioning, and iteration, partnering closely with electrical and software engineers to deliver safe, flexible, high-uptime test cells. In this role, you will Own the mechanical architecture of dynamometer and actuator test cells, including frames, bases, load paths, alignment, guarding, and serviceability. Design dynamometer structures, robotic actuator fixtures, load-motor mounts, couplings, shafts, bearings, adapters, and torque-reaction hardware. Translate robotic actuator test requirements into robust mechanical systems for torque, speed, thermal, durability, backdrive, efficiency, and failure testing. Perform first-principles analysis and simulation for stiffness, strength, fatigue, vibration, thermal growth, critical speed, and safety factors. Create precise, repeatable alignment strategies that protect test articles, load machines, sensors, and couplings. Design modular fixturing that supports rapid changeover across actuator and motor variants without compromising measurement quality. Work closely with electrical engineers on cable routing

About the Team The Agent Safety team works to ensure that increasingly capable AI agents act safely, exercise sound judgment, and remain aligned with user intent. Our mission is to reduce the probability of severe unintended outcomes from increasingly capable AI agents while preserving their ability to act effectively and autonomously. Our work spans three areas: Training: Create training methods, environments and data that teach agents to make better decisions in consequential situations. We turn real-world failures into training signals that prevent similar incidents, and identify precursor behaviors and mitigations to address emerging risks. Measurements: Build evaluations and production metrics that identify emerging risks and measure whether our interventions work. Oversight: Develop oversight and system mitigation mechanisms that reduce harmful actions while preserving useful autonomy (for example future versions of auto-review ). About the Role We’re looking for strong executors with excellent judgment, comfort with ambiguity, and an understanding of frontier model research. You don’t need prior safety or alignment experience, we also welcome people that recently realized that alignment and safety is a critical area to contribute to. 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: Train and evaluate frontier models to reduce harmful or misaligned agent actions, forming clear hypotheses and executing independently through ambiguity. Mine incidents and build scalable measurement, data-processing, and evaluation systems that turn real failures into repeatable safety signals. Collaborate closely with post-training, capabilities, oversight, and pre-training partners to ship research-backed mitigations into large-scale training and agent systems. You might thrive in this role if you: Have demonstrated strength in research engineering, ML en

About the Team The Agent Safety team works to ensure that increasingly capable AI agents act safely, exercise sound judgment, and remain aligned with user intent. Our mission is to reduce the probability of severe unintended outcomes from increasingly capable AI agents while preserving their ability to act effectively and autonomously. Our work spans three areas: Training: Create training methods, environments and data that teach agents to make better decisions in consequential situations. We turn real-world failures into training signals that prevent similar incidents, and identify precursor behaviors and mitigations to address emerging risks. Measurements: Build evaluations and production metrics that identify emerging risks and measure whether our interventions work. Oversight : Develop oversight and system mitigation mechanisms that reduce harmful actions while preserving useful agent autonomy (for example future versions of auto-review ). About the Role This role focuses on oversight and system-level mitigations that enable increasingly capable agents to operate safely and autonomously in real environments. We prioritize building oversight systems that are used in practice today, both internally and externally (see our recent work on action monitoring for codex and former code review ). We also study longer-term questions about how increasingly capable agentis systems can be supervised, constrained, and corrected. We’re looking for a safety&security minded researcher or engineer who can reason rigorously about security boundaries and agent behavior, then build and test practical mitigations. A background in AI control or security is welcome but not required. 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: Design, build, and evaluate system-level controls for agent actions like agent-based review. Plan how they fit in a broader syste

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 the Senior Manager of the Security Posture Management (SPM) team within the Product Security Department , you lead the team that secures GitLab's own software factory: the estate we build and ship from. Your team drives comprehensive, governed rollouts of GitLab's security capabilities across every project, applying our own product the way our customers do, and builds proactive software supply chain security as a first-class capability within Product Security. This is Customer Zero work with real reach. Where the team hits friction adopting our own features at scale, that signal goes straight to Produc

About the Team The Future of Computing Research team is an applied research team within OpenAI’s Consumer Devices group. We study how AI systems perceive people and their surroundings, and we turn that research into capabilities for future products. Our work spans machine learning, sensing, and hardware, with a focus on building systems that work beyond controlled environments. About the Role We’re looking for a machine learning engineer to help shape how future AI systems understand the physical world and the people in it. The role focuses on multimodal perception and authentication, bringing together signals from cameras, microphones, and other sensors. You’ll work with specialized perception models and larger multimodal models, and partner with hardware, firmware, software, and product teams to bring new research into real-world systems. This role is based in San Francisco. We work in the office three days per week and offer relocation assistance. In this role, you will: Research and develop multimodal perception and authentication methods across visual, audio, and other sensing signals. Explore how specialized perception models and larger multimodal models can work together. Design data, training, and evaluation approaches that improve performance in real-world conditions. Study model behavior, robustness, and failure modes across sensing, data, and deployment environments. Integrate and validate new capabilities in real-time or resource-constrained systems. Work with hardware, firmware, software, and product teams to turn research into working systems. You might thrive in this role if you: Have a strong background in computer vision, audio or speech machine learning, multimodal learning, or sensing. Have experience developing specialized machine learning models, larger multimodal models, or both. Have brought research ideas into practical systems, prototypes, or products. Know how to design experiments, build evaluations, and investigate model behavior. Have wo

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. Senior Software Engineer, Trust (TPRM) - Job Description As a Senior Software Engineer on Vanta's Trust TPRM team, you'll build the full-stack product experiences and underlying data infrastructure that help enterprises manage vendor risk at scale — working across teams focused on vendor lifecycle management and vendor monitoring. Vanta's Trust TPRM (Third-Party Risk Management) team is building the products that make vendor risk management seamless for security and procurement teams. From vendor onboarding and lifecycle management to continuous monitoring and procurement integrations, we're creating the platform that helps Vanta customers understand, track, and mitigate third-party risk — a fast-growing, business-critical capability for modern enterprises. As a Senior Software Engineer, you'll contribute as a core member of either the Vendor Lifecycle or Vendor Monitoring Experience team. You'll design and ship full-stack features that directly shape how customers manage vendor relationships, collaborate with product and design partners, and bring real engineering ownership to a product area that's growing quickly within Vanta. What you’ll do as a Senior Software Engineer at Vanta: Design, build, and maintain full-stack features across the TPRM product surface, including vendor onboarding, lifecycle management, and monitoring workflows Contribute to the vendor data model and core platform abstractions that power TPRM products Write clean, well-tested code and actively participate in code reviews; uphold engineering quality standards Engage in architecture discussions and contribute to technical decision-making within your team

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. About the Team The CI and CD Foundation team is the backbone of our engineering velocity. Our mission is to engineer and deliver a CI/CD ecosystem that streamlines the integration and delivery of our core client code—including the Game Engine, Studio, and User Apps. We are laser-focused on three goals: enhancing overall build reliability, maximizing developer productivity, and ensuring consistent software quality. We’re building and improving pipelines and tools to transform SDLC in the age of AI-driven software development. The Role As a Principal Software Engineer on the CI/CD Foundation team, you will serve as the chief technical strategist and architect responsible for transforming how Roblox builds, tests, and ships code at massive scale. Our build and delivery ecosystem handles immense complexity: decades of C++ game engine code, extensive Lua applications, complex native platforms, and a sprawling monorepo with massive, growing test suites. You will lead the technical vision to modernize, decouple, and accelerate this ecosystem—driving radical improvements across our Local Dev Inner Loop (pre-commit/pre-push), CI (PR validation, speculative execution, merge queues), and CD (OTA

The Assurance, Risk and Compliance (ARC) Initiatives team at MongoDB owns the governance and delivery of key cross-functional security risk and compliance initiatives. The team designs and executes programs that support compliance audits, risk assessments, common control frameworks, operating cadences, and executive reporting that strengthen the organization’s assurance, risk management and compliance objectives. The policy and controls governance pillar is responsible for the structure, standards and operating mechanisms that keep MongoDB’s security policies, standards, procedures, and controls governance processes current, aligned, auditable and scalable across the organization. This includes ownership of the policy lifecycle, common controls framework governance, issue management, and the review cadences and cross-functional coordination needed to maintain strong governance maturity and audit readiness. This role sits under the Assurance, Risk and Compliance function within the Global Security Office and reports to the Director of ARC Initiatives. This role will be based remotely in the United States Responsibilities: Scope of Ownership Policy governance program ownership, including policy lifecycle management, documentation standards, review and approval cadences, change tracking, and exception governance Controls governance ownership, including common controls framework lifecycle management, control harmonization, framework mapping, and processes that support audit readiness and scalable control oversight Governance over supporting systems and workflows, including Jira, GRC tooling, documentation repositories, and reporting structures, that enable consistent execution and visibility Issue management and remediation governance, including intake, triage, tracking, and reporting for timely closure of findings Executive-ready reporting and metrics for policy health, controls maturity, policy exceptions and broader program effectiveness Program Leadership Own

Note: if you are an intern, new grad, staff, frontend or fullstack applicant, please do not apply using this link and visit our jobs page for those specific postings. Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies — from the world's largest enterprises to the most ambitious startups — use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the Organization Payments and Risk Sub-orgs: Link and OCS, Payments Acceptance, Risk The Payments organization focuses on developing products and platforms that enable users to accept payments from customers efficiently. This includes building APIs for processing payments, enabling regional, non-card payment options, and extending Stripe's capabilities to make it easy for businesses to accept in-person payments. Optimized Checkout and Link teams work to create best-in-class checkout experiences that enhance customer satisfaction and drive merchant conversion rates. The Risk Engineering team develops products that minimize financial and regulatory risks while ensuring a seamless user experience, thereby safeguarding Stripe's brand and financial stability. Team Matching: Exact team matching for one of the sub-teams will begin during final stages. Please note we may also consider you for different orgs based on your experience, location, etc. What you'll do We're looking for backend engineers who want to make an impact on managing money at a global scale with a passion for building ergonomic APIs. Our team collaborates with many cross-functional teams — from Infrastructure to Product — to deliver innovative solutions that address evolving user needs. Responsibilities

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a researcher working on Frontier Evals & Environments, you will help build north star model environments to drive progress towards safe AGI/ASI. Your work will directly guide the research programs of the most ambitious training runs happening at OpenAI. Some prior open-sourced evaluations built by researchers in this role include GDPval , SWE-bench Verified , MLE-bench , PaperBench , and SWE-Lancer . If you are interested in feeling firsthand the fast progress of our models, and steering them towards good outcomes, this is the role for you. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you might Create ambitious RL environments to push our models to their limits, and measure frontie

About the Team OpenAI’s Platform team powers how millions of developers and enterprises build with our models. We provide APIs and agentic solutions used by global startups and fortune 500s. We work closely with product, engineering, design, and go-to-market to build a world-class platform that pushes the frontier of AI capabilities. About the Role As a Data Scientist on the Platform team, you will drive a data-driven culture for OpenAI’s API and B2B solutions. You’ll define the metrics that matter for developer success and enterprise value, measure the impact of new models and features, and partner with PMs and engineers to improve model quality, reliability, latency, and cost. Your work will shape how thousands of products adopt agentic AI. 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 Embed with the Platform product team as a trusted partner, uncovering ways to improve developer experience, reliability, and usage growth Define north-star metrics across the developer funnel (activation, retention, growth), as well as latency/cost guardrails for new features and models Design and interpret A/B tests and controlled rollouts (e.g., new model versions, pricing/limits, new API features, new B2B products) Build source-of-truth dashboards and self-serve data tools for product, engineering, and go-to-market teams Translate product learnings into actionable feedback for Research (e.g., failure modes, eval gaps, model response quality) You might thrive in this role if you have 5+ years in a quantitative role in ambiguous, high-growth environments (platforms, APIs, or B2B products a plus) Depth in SQL and Python, with a track record proposing, designing, and running rigorous experiments Experience defining and operationalizing metrics from scratch (including reliability/latency/cost and safety) Strong cross-functional communication with PMs, enginee

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team Stripe’s global demand campaigns team delivers marketing campaigns that drive awareness and engagement for our audiences, solutions, and products worldwide. Working closely with sales and marketing teams, our campaigns support Stripe’s larger business objectives and deliver impact. We build, deliver, monitor, and evolve campaign delivery across a broad suite of content, tactics, and channels. Using a broad suite of metrics, we continuously measure our work and refine our strategies to improve outreach, enhance the customer journey, and support revenue growth for the organization. What you’ll do In this role, you'll quarterback the integrated campaign strategies, plans, and playbooks focused on Stripe’s stablecoin and crypto products (including Bridge). You'll champion the needs of the core audiences for this product area, holding deep market and audience insight and direct business accountability. You'll lead a large, global, cross-functional workstream to build campaign strategies and content, then work with regional teams to craft local strategies and to deliver activations through integrated channels. You'll capture performance against all of your efforts, analyze results, and share learnings to drive continuous improvement and impact. Ultimately, you'll be accountable for acquisition, engagement, and pipeline growth. The ideal candidate Excels in leading and driving large, complex, global campaigns or programs Has strong analytics skills

Step into a mission where what you do truly matters! At Leidos, innovation is at the heart of everything we do. Powered by a team as diverse as it is talented, we're driven by a shared passion for delivering bold solutions that fuel our customers' success. We believe in empowering our people, giving back to our communities, and leading with sustainability. Every action we take is grounded in integrity and a steadfast commitment to doing what’s right—for our customers, our teams, and the world around us. Our Mission, Vision, and Values aren't just words—they're the compass guiding our journey toward a brighter future. If this sounds like the kind of environment where you can thrive, keep reading! Leidos is thrilled to share an exciting opportunity for a mission-focused Intelligence Analyst (AI/ML) at Joint Base Langley–Eustis in Hampton, VA! This is a chance to directly shape the next generation of Air Force intelligence professionals through cutting-edge AI/ML, data analytics, and automation training. Candidates must currently hold an active TS/SCI clearance . What You’ll Do: Help empower the ACC A2 mission by delivering high-impact instructional support: Assist in providing instructional support services that will allow the A2 staff to achieve its mission: Independently deliver and maintain formal classroom and virtual instruction on tool-agnostic AI/ML concepts, Large Language Models (LLMs), Robotic Process Automation (RPA), and advanced data analytics, ensuring established courseware remains current with standard DoD and IC applications. Execute tiered role-based training, adapting delivery to meet varying student proficiency levels—ranging from foundational AI/ML user adoption and awareness to intermediate prompt engineering and automated workflow creation. Instruct personnel on the underlying methodologies of AI/

About the Role The AI Deployment Manager (ADM) - Pilots is a customer-facing role responsible for leading structured, time-bound enterprise AI pilots from initial scoping through final executive readout. This role is focused on helping customers evaluate OpenAI’s products in real-world contexts, identify high-value use cases, and generate clear, decision-ready signals tied to business value. You will design and lead pilot engagements that drive activation, sustained usage, and measurable impact across ChatGPT Enterprise, Codex, and adjacent workflows. This includes partnering with customer stakeholders to define success criteria, guiding users from experimentation to real adoption, and translating pilot outcomes into clear recommendations that support expansion or purchase decisions. This role requires strong judgment, the ability to operate in ambiguity, and a consistent focus on connecting technical capabilities to business outcomes. You will regularly engage both executive stakeholders and working teams, adapting your approach to meet customers where they are and move them forward. In this role, you will: Own the design and execution of enterprise AI pilots, including scoping, cohort definition, and success criteria aligned to a clear commercial decision. Identify and prioritize a small set of high-impact use cases that can generate credible signal within a 30–45 day pilot. Drive activation and sustained engagement across pilot cohorts through targeted enablement, office hours, and workflow-level coaching. Monitor pilot performance and adapt in real time, diagnosing gaps in engagement, use case traction, or stakeholder alignment. Translate pilot signals into clear, executive-ready recommendations, including whether and how the customer should expand. Navigate customer constraints such as security, data access, and competing tools while maintaining pilot momentum. Partner closely with ADs, SEs, and customer stakeholders to align on scope, risks, and next steps. Ca

About the Team pAGI Infra team builds and operates the systems that make large-scale model training and evaluation reliable, efficient, and easy to run. Our work spans distributed training infrastructure, inference and grading platforms, compute scheduling, and research tooling. We partner closely with researchers and engineering teams to turn new research needs into dependable infrastructure, improve GPU efficiency, and shorten the path from an experiment to a validated model. About the Role We’re looking for an AI Systems Engineer to help scale the infrastructure behind our training and evaluation workflows. You’ll own projects from identifying bottlenecks and designing solutions through deployment and operation. The work combines distributed systems engineering, performance optimization, and close collaboration with researchers. You might build a shared grading service, improve resource allocation across workloads, or bring a new training stack into production — directly improving how quickly and reliably research moves forward. In this role, you will: Build and operate infrastructure for large-scale training and evaluation, improving reliability, throughput, and resource efficiency. Develop shared inference and grading platforms with automated capacity management, health monitoring, and visibility into performance. Improve compute scheduling and resource allocation to reduce idle GPU time and help workloads recover quickly from failures. Diagnose bottlenecks across training, inference, and orchestration, and work across teams to improve end-to-end performance. Build self-service tools, automated validation, and observability that help researchers launch experiments, diagnose issues, and compare results with less manual intervention. You might thrive in this role if you: Are excited about the potential of personal AGI and want to build the infrastructure that enables it. Have strong software engineering fundamentals and experience building or operating large-scal