Large Enterprise Account Executive in United States

What you’ll do Act as the technical lead for large parts of the scanner platform: system architecture, codebase structure, and long-term maintainability. Own core runtime foundations: distributed control, state management, fault handling, and reliability. Drive engineering rigor: testability, code quality, review standards, performance regression prevention, and release processes. Build robust observability: logs, metrics, traces, and replayable diagnostics (with privacy constraints). Collaborate with hardware and recon/ML teams to define interfaces, data contracts, timing/synchronization, and failure modes. Lead complex refactors (e.g., message passing / RPC boundaries, modularization, concurrency model) without halting forward progress. What we’re looking for Deep software architecture experience for real-world systems: robotics, instrumentation, medical devices, or other complex distributed products. Strong Python and concurrency background (asyncio, multiprocessing, profiling, performance engineering). Track record of shipping systems that are observable, debuggable, and resilient. Strong technical leadership: clarity, pragmatic trade-offs, and mentoring. Useful experience Building but rock-solid systems: clear interfaces (gRPC/protobuf or equivalent), strong state modeling, and failure handling. High-leverage engineering habits on a lean team: good tests, CI, reproducible dev environments, and fast code review. Practical performance + concurrency work in Python (asyncio, profiling, multiprocessing) and comfort debugging distributed behavior. Security-minded device software: safe defaults, encrypted data paths, and disciplined handling of PII/PHI. Operational thinking: remote updates/management, excellent logging, and diagnostics that make real hardware debuggable.

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. As a Manager, Data Center Operations, you'll help us scale our Core Data Center and hardware infrastructure at a time of incredible growth for our business. At Roblox, you'll have boundless opportunities to shape the future of the Imagination Platform™ and demonstrate your passion for delivering thoughtful solutions in front of a global audience. If you know what it takes to build and operate hardware infrastructure that can sustain millions of concurrent players year-round and you take play as seriously as we do, you'll fit right into our highly experienced and ever-expanding engineering team. You will report to the Senior Manager of Data Center Operations. This will be a position based in Goodyear, AZ. You will: Develop and maintain the Core Data Center and hardware infrastructure to meet the large-scale and real-time requirements of our Imagination Platform™ to ensure our community has an awesome experience anywhere in the world. This includes all aspects of the server, network infrastructure, power, and environmental monitoring. Lead a growing team of data center engineers focusing on rack deployments, hardware troubleshooting and break-fix, and decommissioning. Identify and solve criti

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

The Regulatory Risk Group Manager is accountable for management of complex/critical/large professional disciplinary areas. Leads and directs a team of professionals. Requires a comprehensive understanding of multiple areas within a function and how they interact in order to achieve the objectives of the function. Responsible for driving customer remediation analytics to completion including execution and validation. This position will be part of the USCC Centralized Customer Remediation Team (CCRT). The objective of the USCC CCRT is to quickly assess and identify customer impacts and ensure remediation is completed promptly with the appropriate detailed documentation required by Internal Audit and the Regulators. These activities will be conducted in close partnership with the Issue Owners and Managers within U.S. Consumer Cards. Excellent communication skills are required to negotiate internally, often at a senior level. Highly developed communication and diplomacy skills are required, to guide, influence, and convince others, in particular colleagues in other areas and occasional external customers. This role is a people manager role with full management responsibility of a team or multiple teams, including management of people, budget and planning, to include performance evaluation, compensation, hiring, disciplinary actions and terminations and budget approval. Responsibilities: Manage a team of remediation analysts and associated book of work for the team. Perform training, reviews, coaching, and mentoring of staff. Over-sees, designs, and manages client remediation population and impact analyses for USCC owned and impacted issues, including those that are Regulatory. Provide expertise and guidance related to the USCC remediation processes and policies, partners with other department leaders to define, prioritize, and execute remediation programs. Create comprehensive documentation that confo

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE Baseten’s Inference Stack team builds the distributed runtime that powers large-scale LLM inference across our platform. We operate at the intersection of distributed systems, model performance, infrastructure, and developer experience. We enable customers to deploy and operate cutting-edge LLM models with industry-leading performance, scalability, reliability, and ease of use. As a Software Engineer on the Inference Stack team, you’ll work across the stack - from the developer experience customers use to deploy models, the libraries used for features like tool calling and reasoning, all the way down to the systems we use to orchestrate deployments in Kubernetes and route traffic efficiently. This is an ideal role for engineers who enjoy owning systems in production, solving hard integration problems, and making complex infrastructure simple and reliable for users. EXAMPLE INITIATIVES Blog Posts https://www.baseten.co/blog/nvidia-dynamo-day-baseten-inference-stack/ https://www.baseten.co/blog/how-baseten-achieved-2x-faster-inference-with-nvidia-dynamo/ https://www.baseten.co/blog/how-baseten-multi-cloud-capacity-management-mcm-powers-cloud-self-hosted-and-hybr/#comparing-deployment-options-cloud-vs-self-hosted-vs-hybrid RESPONSIBILITIES Develop infrastructure and orchestration systems for deploying and managing large-scale distributed LLM inference Work across the stack, from customer-facing features to low-le

What you’ll do Design and implement secure cloud pipelines that ingest very large scan datasets (multi-terabyte), reliably and resumably. Build orchestration for GPU-accelerated reconstruction and analysis with strong retry semantics, idempotency, and cost controls. Define end-to-end data lifecycle for medical imaging: raw vs intermediate vs derived artifacts, retention policies, and reproducibility. Implement security + compliance primitives appropriate for HIPAA/PHI: encryption in transit/at rest, key management, least privilege, audit logs, and access reviews. Build operational tooling: monitoring, alerting, runbooks, and incident-driven improvements for a growing device fleet. What we’re looking for Strong experience with cloud batch/queueing/orchestration, storage systems, and data pipeline reliability. Experience shipping production systems that handle large data volumes and failure-prone networks. Practical security mindset (least privilege, secrets, audit logging) and comfort operating in compliance-constrained environments. Useful experience Building reliable data pipelines at scale (queues/orchestration, resumable uploads, GPU batch execution) with strong observability. Security + privacy by default: encryption, least-privilege access, auditing, and practical HIPAA/PHI guardrails. Owning the “boring” backend details that keep a lean team moving: schemas/migrations, cost controls, retries, and runbooks. Understanding compute tradeoffs across hardware options, and specifying appropriate cloud resources.

We are seeking a visionary Answer Engine Optimization Lead to spearhead our Large Language Model (LLM) and AI platform visibility strategy (e.g., ChatGPT, Claude, Google AI Overviews, Perplexity). Reporting into the Director of Marketing Acquisition, this role will be responsible for expanding our brand authority, maximizing developer mindshare, and driving new customer acquisition by optimizing MongoDB’s presence within LLM and answer engine responses. If you thrive at the intersection of technical content architecture, structured data, community advocacy, and AI-era discovery—and you want to lead a team on the front lines of defining the next wave of search experience optimization—this is a critical leadership role designed to accelerate target audience awareness and Product-Led Growth (PLG). This role will be based remotely in the United States. Key Responsibilities Define & Execute AEO Strategy: Design and own MongoDB’s global LLM visibility growth initiatives. Develop and execute strategies focused on increasing the citation share, sentiment, and accuracy of MongoDB across various technical developer audiences and agentic AI models Team Leadership: Oversee and scale a high-performing team of SEO, AEO, and content optimization professionals, fostering a culture of rapid experimentation in the AI search space Technical Information Architecture: Collaborate with Product, Engineering, and Documentation teams to optimize MongoDB’s digital footprint for LLM crawlers. Impose best practices for structured data, schema markup, knowledge graphs, and API/documentation accessibility to facilitate flawless RAG (Retrieval-Augmented Generation) ingestion UGC Response & Community Advocacy: Coordinate a multi-team framework (including Developer Relations and Support) to ensure timely, high-quality, and LLM-friendly insights are present on critical developer watering holes (e.g., Reddit, Stack Overflow, GitHub, Wikipedia). Leverage "build in public" tactics to organicall

About the Team The compute infrastructure team runs the GPU fleet and large-scale compute clusters that serve the models backing ChatGPT and the API, while also supporting training workloads for our next generation models. We operate a large, modern GPU fleet and provide a unified platform for other OpenAI teams to seamlessly run production Applied AI and Research training workloads. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role You’ll own the hands-on and automation work that brings WAN, fiber, carrier, and cloud-interconnect circuits into service. Partner with network engineers, fiber providers, cloud service providers, colocation teams, and data-center technicians to move each connection from ordered and patched to verified, stable, and ready for handoff. You’ll own Layer 1 troubleshooting and circuit bring-up while building workflows that translate reliable system or model output into precise, approved technician actions, capture field feedback, and drive each connection to a green-port handoff. The right person combines strong physical-networking judgment with practical automation skills: patch-panel and port mappings, optics and light levels, provider coordination, structured operational data, API or scripting workflows, and human-in-the-loop LLM tooling. Responsibilities Own Layer 1 activation and restoration for carrier circuits, dark fiber, wavelengths, Ethernet handoffs, and dedicated cloud interconnects across data centers and points of presence. Reconcile complete A-side/Z-side as-builts: circuit IDs, LOAs/CFAs, carrier demarcations, MMR/ODF/MDF and patch-panel positions, fiber pairs, cross-connects, optics, and device ports. Investigate no-light, low-light, wrong-port, link-flap, and error-rate issues across providers and CSPs; isolate continuity, dirty connectors, polarity, incorrect patching

About the Team The compute infrastructure team runs the GPU fleet and large-scale compute clusters that serve the models backing ChatGPT and the API, while also supporting training workloads for our next generation models. We operate a large, modern GPU fleet and provide a unified platform for other OpenAI teams to seamlessly run production Applied AI and Research training workloads. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role You will be part of an engineer-first TPM team as a Technical Program Manager for Compute Infrastructure who owns the end-to-end delivery of large-scale GPU clusters, partnering with engineers to bring clusters online across external providers and partners. You’ll run a broad, parallel portfolio spanning hardware, networking, power, and cooling—driving execution, risk management, and crisp alignment from working teams through leadership to deliver production-ready capacity at scale. 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: Lead end-to-end delivery of both New Compute SKUs and large-scale GPU clusters across an external partner ecosystem while supporting capacity planning for training and inference. Ability to contextually drive multi-threaded bring-up programs spanning hardware, networking, power, and cooling—owning plans, dependencies, and critical paths. Interface with chip providers to derisk long-term onboarding to new hardware platforms by working across kernels, comms, hardware, and scheduling engineering teams. Build and operationalize program mechanisms (roadmaps, milestones, risk registers, runbooks) that make delivery predictable at massive scale. Partner with engineering to improve cluster turn-up reliability, repeatability, and automation

About the Team OpenAI's Training team is responsible for producing the large language models that power our research, our products, and ultimately bring us closer to AGI. Achieving this goal requires combining deep research into improving our current architecture, datasets and optimization techniques, alongside long-term bets aimed at improving the efficiency and capability of future generations of models. We are responsible for integrating these techniques and producing model artifacts used by the rest of the company, and ensuring that these models are world-class in every respect. Recent examples of artifacts with major contributions from our team include GPT4-Turbo, GPT-4o and o1-mini. About the Role As a member of the architecture team, you will push the frontier of architecture development for OpenAI's flagship models, enhancing intelligence, efficiency, and adding new capabilities. Ideal candidates have a deep understanding of LLM architectures, a sophisticated understanding of model inference, and a hands-on empirical approach. A good fit for this role will be equally happy coming up with a creative breakthrough, investing in strengthening a baseline, designing an eval, debugging a thorny regression, or tracking down a bottleneck. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design, prototype and scale up new architectures to improve model intelligence Execute and analyze experiments autonomously and collaboratively Study, debug, and optimize both model performance and computational performance Contribute to training and inference infrastructure You might thrive in this role if you: Have experience landing contributions to major LLM training runs Can thoroughly evaluate and improve deep learning architectures in a self-directed fashion Are motivated by safely deploying LLMs in the real world Are well-versed in the state of the art tran

About the Team OpenAI’s Industrial Compute team is responsible for building and scaling large-scale compute capacity across first-party data centers, strategic partners, and industrial infrastructure environments. We focus on converting power, land, hardware, and operational execution into reliable compute capacity that can support frontier AI training and inference workloads. This team operates at the intersection of infrastructure delivery, hardware systems, utilities, supply chain, and capacity strategy—ensuring OpenAI can scale compute faster than traditional models allow. About the Role We are seeking a Tokens-as-a-Service (TaaS) Lead to drive the end-to-end conversion of industrial-scale infrastructure investments into usable token capacity for OpenAI workloads. In this role, you will own execution across complex compute programs where raw infrastructure capacity must be transformed into operational GPU throughput. You will coordinate across data center delivery, power, networking, hardware deployment, workload enablement, finance, and external partners to ensure capacity becomes productive tokens as quickly and efficiently as possible. This role is ideal for someone who can bridge physical infrastructure delivery with compute utilization outcomes. Success requires strong systems thinking, elite program leadership, and the ability to drive accountability across internal teams and strategic partners. In this role, you will Lead Tokens-as-a-Service programs across industrial compute environments, including first-party and partner-owned capacity. Convert delivered power, space, and hardware capacity into production-ready token throughput. Build integrated execution plans spanning construction, power energization, rack deployment, networking, cluster readiness, and workload onboarding. Partner with infrastructure engineering, hardware, networking, finance, supply chain, and operations teams. Drive external providers, EPCs, OEMs, utilities, and strategic partners t

About the Team The Stargate team is responsible for building the physical infrastructure that powers large-scale AI systems. We design and deliver next-generation data centers optimized for dense compute clusters, advanced networking, and rapidly evolving hardware platforms. This work sits at the intersection of hardware engineering, systems architecture, and infrastructure execution—translating cutting-edge compute roadmaps into scalable, production-ready environments. Our teams partner across silicon vendors, server and storage OEMs, networking teams, and data center engineering organizations to bring new capacity online quickly, reliably, and at global scale. About the Role We are seeking a CPU & Storage Technical Lead to define and drive the server compute and storage architecture strategy for Stargate infrastructure. In this role, you will own technical direction across CPU platforms, memory configurations, local and disaggregated storage systems, and their integration into large-scale AI clusters. You will evaluate vendor roadmaps, lead platform tradeoff decisions, and ensure compute and storage systems are optimized for training, inference, and supporting services. You will work cross-functionally with hardware engineering, performance modeling, networking, supply chain, and deployment teams, as well as external partners such as AMD, Intel, OEMs, ODMs, and storage vendors. This is a highly strategic role for someone who can operate deeply at the component level while also driving long-range infrastructure decisions. Key Responsibilities Own CPU and storage technical strategy for Stargate compute infrastructure across current and future generations. Evaluate CPU platforms across performance, efficiency, memory bandwidth, PCIe topology, cost, and roadmap alignment. Define storage architectures for AI environments, including boot media, local NVMe, shared storage, caching tiers, metadata services, and high-performance data pipelines. Drive server platform de

About the Team Life sciences is one of the clearest areas where advances in intelligence can meaningfully benefit the world at large. The OpenAI Life Sciences team works at the intersection of advancing frontier life sciences model capabilities and building products to help scientists accelerate their research and leverage the full potential of AI for scientific work. Rosalind Workbench brings together the scientific tools, data sources, interactive biology file viewers and core life sciences workflows into a central environment to help scientists investigate questions, design experiments, analyze results, and advance discovery. Rosalind Workbench can be used with any OpenAI model, including GPT-Rosalind--our dedicated life sciences model, which combines frontier reasoning with specialized tool orchestration across medicinal chemistry, genomics, wet-lab assistance, and other scientific applications. Our long term vision is for teams of agents to work together across these domains, giving researchers access to broader expertise and the ability to pursue more ambitious scientific questions. About the Role We’re looking for a Product Manager to shape Rosalind Workbench for life sciences. You will own product strategy and execution, working directly with researchers in academic labs, biotech, and pharma to understand where AI can meaningfully improve their work. You’ll partner with engineering, research, design, and customer-facing teams to turn emerging capabilities into intuitive products that scientists return to. This role calls for strong product judgment, depth in life sciences, and the ability to move from an ambiguous research problem to a focused, shippable experience. In this role, you will have the opportunity to define the future of AI guided scientific discovery and build the capabilities and tools that help advance the scientific frontier for researchers and help increase the accessibility of model intelligence for scientific use. This is a chance to shape

We're looking for a Senior Mechanical Engineer for Midjourney Medical — from precision electromechanical assemblies up to the large-scale structures and mechanisms that hold everything together and make it move. This role spans the full range of scale: one week you might be refining a compact transducer mount, the next you're architecting a structural frame or designing the motion system that positions hardware within it. This is a hands-on role on a small cross-functional team. You'll take problems from whiteboard sketch to working hardware yourself — designing in CAD, prototyping in the shop, testing, iterating, and integrating with research teams, electrical and software engineers along the way. We move fast and expect you to drive your own work: identifying what needs to happen next, making sound engineering calls without waiting for permission, and shipping hardware that works. What you'll do Own parts of the mechanical systems end to end — structures, mechanisms, and electromechanical integration Design large-scale structures: frames, weldments, enclosures, and support systems, with attention to stiffness, weight, manufacturability, and serviceability Design mechanisms: linkages, motion stages, actuation systems for precise, reliable positioning and articulation Integrate transducers, electronics, cabling, and thermal management into large physical systems Perform engineering analysis (tolerance stack-ups, structural/FEA, mechanism kinematics) to de-risk designs before committing to hardware Build and test relentlessly — 3D printing, rapid prototyping, and hands-on fabrication are core to how you'll validate designs Select parts and materials for system-level integration, balancing performance, cost, and lead time Drive projects independently from concept through validation, and collaborate closely with a small cross-disciplinary team to hit project goals What we're looking for Bachelor's degree in Mechanical Engineering or a related field 5+ years of experien

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 . At Pinterest, our mission is to bring everyone the inspiration to create a life they love, and as a Technical Program Manager focused on Identity, you will play a critical role in protecting that experience. You will sit at the intersection of account integrity, abuse prevention, and safety for sensitive populations (including teens), ensuring that people can confidently discover ideas without worrying about account compromise, spam, or harmful content. You will partner closely with Engineering, Product, Data Science, and Operations to define strategy and deliver large, multi-year programs across identity, account access, bots and automation abuse, age assurance, and safety controls. This is a highly cross-functional role with broad visibility and impact across the company. What you’ll do: Lead company-level Identity & Product Safety p