Sales Engineer 2 in United States

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 Senior Software Engineer across our Identity, Data Security and Trust organization. These teams builds the security backbone of Snowflake — enabling customers to confidently bring their most sensitive data and workloads to the Data Cloud, empowering every Snowflake engineer to deliver the most secure platform at scale, and giving customers the tools to monitor, achieve, and maintain a strong security, governance, privacy, and compliance posture. As the agentic era accelerates, these teams are at the forefront of building AI-native security capabilities that protect the world's data. AS A SENIOR SOFTWARE ENGINEER AT SNOWFLAKE, YOU WILL: Design and implement critical AI security capabilities — including controlled, audited agent workflows, MCP server and client security, agent identity frameworks, and admin guardrails — that form the foundation for secure agentic enterprise adoption Build and evolve foundational identity and access management systems, including authentication protocols, SSO integrations, multi-factor authentication, OAuth/OIDC, SAML, SCIM, and fine-grained RBAC that scales to millions of objects and users Design and develop core security infrastructure spanning secret management, key management, service identity, and end-to-end encryption acro

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. About Dynamic Tables Dynamic Tables (DTs) are Snowflake's declarative streaming transformation primitive. Customers define a SQL query and a freshness target; Snowflake handles the rest: orchestrating refreshes, maintaining snapshot consistency across a DAG of dependencies, and automatically incrementalizing the computation so that cost scales with what changed. Dynamic Tables is one of the fastest growing products at Snowflake and is a core part of Snowflake’s Data Engineering strategy. The Dynamic Tables performance team is responsible for making incremental refresh fast, predictable, and cost-efficient across increasingly complex query shapes. As a Staff Engineer on this team, you will own the technical direction for critical performance initiatives and be a force multiplier for the engineers around you. What You'll Do Lead the design and implementation of performance improvements to the incremental view maintenance engine, including multi-join incrementalization, novel incrementalization semantics, incremental window functions, and stacked operations. Help define the roadmap for the incremental view maintenance engine, identifying key performance, scalability, and correctness milestones, prioritizing high-impact enhancements, and aligning technical investments with prod

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. We are looking for a motivated Deep Learning engineer to bring advanced communication technologies into AI stacks, including PyTorch, TRT-LLM, vLLM, SGLang, JAX, etc. You will be working with the team that created communication libraries like NCCL, NVSHMEM & technology like GPUDirect -- for scaling Deep Learning and HPC applications. Your customers will have diverse multi-GPU demands, ranging from training on scales up to 100K GPUs to inference down at microsecond latency. Communication performance between the GPUs has a direct impact on AI applications. Your work in AI toolkits will make all of those easier for the community. This is an outstanding opportunity for someone with an AI background to advance the state of the art in this space. Are you ready to contribute to the development of innovative technologies and help realize NVIDIA's vision? What you will be doing: Integrate new communication libraries features in AI frameworks: from PoC to performance analysis to production Perform deep analysis of AI workloads and frameworks to identify multi-GPU communication requirements and opportunities. Collaborate hands-on with teams working on the latest AI models. Improve AI compilers to hide communications or perform automatic fusion. Conduct in-depth AI workload performance characterization on multi-GPU clusters. Design fault-tolerant and elastic solutions for large-scale or dynamic AI workloads. Author

We're looking for an Engineering Manager II to own and grow the Observability Pipelines engineering org at a pivotal moment in the product's lifecycle. Observability Pipelines is Datadog's on-premise, vendor-agnostic telemetry pipeline product, with a lot still to build as it grows and scales. It sits at the center of a fast-consolidating market, is central to Datadog's data pipeline optimization story for Logs and Metrics customers. This is a build-and-scale opportunity: you'll grow the management and technical leadership layers, co-own the roadmap with Product, and define how this org operates as it continues to expand. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You'll Do: Directly manage the OP org including EM1s across NYC and Paris, set technical direction, and be the connective tissue across a distributed team Build out the management and technical leadership layers as the org continues to grow - today ~20 ICs Partner directly with Product to co-own the roadmap and strategy, helping decide where OP’s engineering investment goes next Set and evolve the operating rhythm across the group: planning cadence, on-call and incident standards, and cross-team alignment Own key cross-org relationships with the SaaS Logs Pipelines team, the BYOC team, and the Vector open-source community Coach managers and senior engineers, and build the succession and growth plans that let the org scale beyond you Who You Are: Experienced managing managers across distributed teams, with a track record of raising the bar on how those teams operate, not just delivering through them Back

As a Staff Application Security Engineer at Datadog, you'll set technical direction for how we approach application security at scale. You'll define the frameworks, methodologies, and architectural patterns that engineering teams across Datadog adopt and apply independently. You're the person others come to when they don't know how to make something secure, and you reliably have an answer. You'll be a point of contact for our most complex security programs, often spanning multiple teams and multiple quarters. The role requires both depth (going very deep on specific problems when needed) and breadth (recognizing patterns across systems and drawing connections that others miss). Partnering closely with teams inside and outside the security org is key to success. You'll help shape the AppSec roadmap and make the case for where investment should go. We use our own platform. Logs, Dashboards, Service Catalog, and APM aren't just things we sell: they're tools the AppSec team uses to build security services, measure adoption of secure defaults, and communicate risk across the organization. AI is also part of the picture. Engineering at Datadog increasingly uses agentic tooling throughout the development lifecycle, and many of the products we ship to customers now include AI-powered features. Both create new attack surfaces, and defining our strategy for addressing them is part of this role. If using Datadog to observe Datadog's own security posture, building impactful tooling, and shaping how we secure AI-powered systems sounds like the right kind of problem, this role is worth a close look. What You’ll Do: Define and drive security standards and secure-by-default solutions, serving as the Application Security subject matter expert. Build security tooling and automation that scales security practices across engineering teams, and implement robust security observability to support our threat detection team with meaningful, actionable security signals. Lead threat mod

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Director, AI Engineering, Transformation Team Overview: The Transformation Team leads strategic change initiatives to reimagine how Mastercard works and scales, simplifies, and accelerates business outcomes. The team partners across leadership, product, technology, and operations to design and implement new organizational models, embed AI across key workflows, drive enterprise-wide transformation programs, improve operating effectiveness, and ensure successful adoption of change. By combining strategy, AI engineering, organizational design, change management, and program execution, the team helps align people, processes, and priorities to support long-term growth and business performance. Role: • This job develops and executes short-term and medium-term strategic plans for AI Engineering across Mastercard, aligning functional initiatives with organizational objectives by modifying existing methods to make significant improvements to existing processes, programs, and/or policies. • Drives the development and execution of short-term functional strategies for AI/ML teams, translating organizational priorities into actionable plans and deliverables. • Collaborates with product and business leaders to translate organizational needs into scalable AI solutions and operational strategies. • Ove

This is a senior individual contributor role for someone who wants to actively shape how Engineering, one of the most important parts of how Datadog develops its people. You'll sit at the center of Datadog's biggest talent bets for Engineering: how we build leaders, define career paths and org design, evolve performance, move talent internally, and plan succession for our most critical roles. You’ll own this work end to end, from the first framing conversation with senior leaders through to delivering a program running at scale. AI is changing how Engineering builds software, and it is changing how People builds the programs that support Engineering too. This role sits at the centre of both: understanding how AI is reshaping engineering roles, skills and structures, and building AI-powered solutions within People to keep pace. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Design and lead complex talent programmes for Engineering, spanning leadership capability, career architecture, org design, performance, internal mobility and succession for critical roles. Partner directly with PBPs and senior leaders to turn ambiguous problems into clear programme goals, design principles and success measures. Help Engineering and People understand and respond to how AI is reshaping roles, skills and ways of working, and translate that shift into practical talent and org design choices. Stay hands-on from concept through to adoption: this is a build and run role, not a strategy and handover role. Work across Enablement, Learning, People Analytics and People Systems so what you build scales and embeds into core people processes. Equip PBPs with frameworks, tools and executive-ready narratives that support real adoption in the business. Operate in ambiguity and influe

Hyliion is committed to creating innovative solutions that enable clean, flexible and affordable electricity production. The Company’s primary focus is to develop distributed power generators that can operate on various fuel sources to future-proof against an ever-changing energy economy. Job Purpose The Senior Manager, Additive Fleet is responsible for the day-to-day performance of Hyliion's laser powder bed fusion (LPBF) printer fleet in Austin, which produces the complex, high-density metal heat exchanger hardware in the KARNO Core. This hardware can only be produced through metal additive manufacturing, so Hyliion's ability to build KARNO at scale depends directly on the health, uptime, and throughput of the fleet. The role leads the technicians and operators who run and maintain the machines, and owns preventive maintenance strategy, machine health monitoring, and decisions on hardware and software upgrades. The fleet runs the full range of Colibrium Additive LPBF platforms, including new machine technology being adopted in real time, and a primary focus is reducing machine-to-machine variation and building repeatable processes across machine models. This is a hands-on leadership role with regular time on the shop floor, and its scope will grow as Hyliion's print capacity scales. AI at Hyliion At Hyliion, AI is core to how we work. We equip every team member with leading AI tools and count on you to use them — to move faster, solve harder problems, and help us realize the full potential of KARNO technology for the world. Duties and Responsibilities Own fleet uptime and drive continuous improvement in machine-to-machine consistency across Hyliion's LPBF printer fleet. Build and maintain a preventive maintenance program across all machines to identify failure modes before they cause downtime. Lead, schedule, and develop the team of technicians and operators who run and maintain the fleet. Develop machine health monitoring us

🚀 About WRITER WRITER is where the world's leading enterprises orchestrate AI-powered work. Our vision is to expand human capacity through superintelligence. And we're proving it's possible – through powerful, trustworthy AI that unites IT and business teams together to unlock enterprise-wide transformation. With WRITER's end-to-end platform, hundreds of companies like Mars, Marriott, Uber, and Vanguard are building and deploying AI agents that are grounded in their company's data and fueled by WRITER's enterprise-grade LLMs. Valued at $1.9B and backed by industry-leading investors including Premji Invest, Radical Ventures, and ICONIQ Growth, WRITER is rapidly cementing its position as the leader in enterprise generative AI. Founded in 2020 with office hubs in San Francisco, New York City, Austin, Chicago, and London, our team thinks big and moves fast, and we're looking for smart, hardworking builders and scalers to join us on our journey to create a better future of work with AI. 📐 About the role AI research at WRITER isn't just about publishing papers — it's about building the scientific foundation that powers some of the most ambitious enterprise AI deployments in the world. As an AI research scientist, you'll be at the center of that work. You'll drive a high-impact research agenda focused on large language models, agentic reasoning, and the system-level capabilities that make AI genuinely useful at enterprise scale. This is a rare opportunity to do research that matters twice over — advancing the field and shipping directly into products used by hundreds of thousands of people every day. We're at an inflection point. Enterprises are moving from experimenting with AI to deeply embedding it across their operations, and WRITER's models are the engine making that possible. The work you do here — on post-training, planning, multi-step reasoning, and agentic workflows — will directly shape how the next generation of enterprise AI behaves, performs, and scales. You

🚀 About WRITER WRITER is where the world's leading enterprises orchestrate AI-powered work. Our vision is to expand human capacity through superintelligence. And we're proving it's possible – through powerful, trustworthy AI that unites IT and business teams together to unlock enterprise-wide transformation. With WRITER's end-to-end platform, hundreds of companies like Mars, Marriott, Uber, and Vanguard are building and deploying AI agents that are grounded in their company's data and fueled by WRITER's enterprise-grade LLMs. Valued at $1.9B and backed by industry-leading investors including Premji Invest, Radical Ventures, and ICONIQ Growth, WRITER is rapidly cementing its position as the leader in enterprise generative AI. Founded in 2020 with office hubs in San Francisco, New York City, Austin, Chicago, and London, our team thinks big and moves fast, and we're looking for smart, hardworking builders and scalers to join us on our journey to create a better future of work with AI. 📐 About the role AI research at WRITER isn't just about publishing papers — it's about building the scientific foundation that powers some of the most ambitious enterprise AI deployments in the world. As an AI research scientist, you'll be at the center of that work. You'll drive a high-impact research agenda focused on large language models, agentic reasoning, and the system-level capabilities that make AI genuinely useful at enterprise scale. This is a rare opportunity to do research that matters twice over — advancing the field and shipping directly into products used by hundreds of thousands of people every day. We're at an inflection point. Enterprises are moving from experimenting with AI to deeply embedding it across their operations, and WRITER's models are the engine making that possible. The work you do here — on post-training, planning, multi-step reasoning, and agentic workflows — will directly shape how the next generation of enterprise AI behaves, performs, and scales. You

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the Role We're looking for an AI-native product growth lead to own Replit's entire paid acquisition and lifecycle marketing engine as the single DRI. This is an IC role for someone who builds systems, not just campaigns. Someone who uses AI and automation aggressively to do what traditionally requires an entire team. You don't need an engineering background. You need the instinct to build: when you see a repetitive task, you reach for Replit or an API before you reach for a spreadsheet. You'll have data science and data engineering partners for infrastructure and modeling, and brand marketing will set creative direction. Your job is to turn that direction into a closed-loop optimization system: a self-improving system that turns performance data into better creative, optimizes spend across channels in near-real-time, and compounds every insight so nothing learned is ever lost. Each cycle, the system gets smarter. That's the engine you'll build and own. The ideal candidate has deep channel expertise across paid search, paid social, and lifecycle, but their real edge is building AI-powered workflows that scale creative production, automate measurement, and compound institutional knowledge. You Will Own full-funnel performance marketing across paid search & social, ASO, and lifecycle Build a self-improving creative engine: AI-driven ad generation, testing, and iteration that scales without scaling headcount Maintain a persistent knowledge layer so every experiment, result, and creative insight compounds automatically into the next cycle Own conversion signal quality end-to-end: right events, right audiences, right attribution, partnering with DE on the infrastructure Run a structured experimentation program wher

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. We are looking for a Security Operations Lead (SOC Lead) to build, mature, and operate our 24/7 detection and response capabilities across a modern cloud-native and AI-driven environment. This role leads the global SOC function—monitoring, SIEM ownership, detection engineering, alert triage, and operational readiness—while also evaluating and integrating emerging AI-based SOC products and autonomous response platforms . You will oversee monitoring across multi-cloud environments (GCP primary, AWS/Azure secondary), Kubernetes, SaaS services, endpoints, developer tools, and AI workloads . You’ll collaborate closely with Cloud Security, Compliance/GRC, SRE, Platform Engineering, IT/Endpoint teams, and AI Infrastructure to ensure our detection strategy scales and stays ahead of evolving threats. This is a hands-on leadership role perfect for someone who wants to shape the SOC of the future while solving complex challenges in a high-scale AI setting. What You’ll Do SOC Leadership & 24/7 Monitoring Lead, mentor, and scale a global SOC team responsible for 24/7 monitoring, alert intake, triage, correlation, and escalation. Build operational rigor: processes, runbooks, SLAs, metrics, and quality standards for high-scale environments. Cover monitoring across: Cloud infrastructure (GCP, AWS, Azure) Kubernetes/GKE/EKS/AKS clusters SaaS platforms (Google Workspace, GitHub, Slack, Okta, etc.) Endpoints (macOS, Linux, Windows) including EDR/XDR telemetry Developer platforms + CI/CD pipelines AI/ML systems and model-serving workflows AI-Based SOC Integration & Innovation Evaluate, adopt, and integrate AI-native SOC technologies for triaging, detection, and correlation Identify opportunities to automate triage, investigations,

About the Role OpenAI’s Industrial Compute organization is responsible for ensuring our compute infrastructure scales efficiently to support millions of users and increasingly sophisticated AI models. We’re looking for a Data Scientist to partner closely with Capacity Systems Engineering, Infrastructure, Product, and Research to optimize inference capacity across our global GPU fleet. This role combines statistical modeling, large-scale data analysis, forecasting, and systems thinking to drive critical decisions around infrastructure investments, performance-efficiency trade-offs, and customer experience. You’ll transform complex operational data into actionable insights that directly influence how OpenAI allocates and scales one of the world’s largest AI compute environments. Key Responsibilities Build statistical and machine learning models to profile and improve GPU utilization, latency, throughput, and overall fleet efficiency. Develop forecasting models for inference demand across products, regions, and model families. Analyze production workloads to identify latency bottlenecks and capacity constraints, highlighting optimization opportunities. Partner with Capacity Systems Engineering to inform infrastructure planning and long-term GPU investment strategies. Design experiments and simulations to evaluate scheduling policies, serving strategies, and infrastructure tradeoffs. Build dashboards and operational metrics that enable leadership to make data-driven capacity decisions. Collaborate with Product, Research, Finance, and Infrastructure teams to align compute planning with business growth and model roadmaps. Communicate technical findings clearly to both engineering teams and executive leadership. Qualifications MS or PhD in Statistics, Computer Science, Operations Research, Applied Mathematics, Economics, or related quantitative discipline (or equivalent industry experience). 5+ years of experience working in the infrastructure data science space. Strong ex

This is a senior individual contributor role for someone who wants to actively shape how Engineering, one of the most important parts of how Datadog develops its people. You'll sit at the center of Datadog's biggest talent bets for Engineering: how we build leaders, define career paths and org design, evolve performance, move talent internally, and plan succession for our most critical roles. You’ll own this work end to end, from the first framing conversation with senior leaders through to delivering a program running at scale. AI is changing how Engineering builds software, and it is changing how People builds the programs that support Engineering too. This role sits at the centre of both: understanding how AI is reshaping engineering roles, skills and structures, and building AI-powered solutions within People to keep pace. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Design and lead complex talent programmes for Engineering, spanning leadership capability, career architecture, org design, performance, internal mobility and succession for critical roles. Partner directly with PBPs and senior leaders to turn ambiguous problems into clear programme goals, design principles and success measures. Help Engineering and People understand and respond to how AI is reshaping roles, skills and ways of working, and translate that shift into practical talent and org design choices. Stay hands-on from concept through to adoption: this is a build and run role, not a strategy and handover role. Work across Enablement, Learning, People Analytics and People Systems so what you build scales and embeds into core people processes. Equip PBPs with frameworks, tools and executive-ready narratives that support real adoption in the business. Operate in ambigu

About the Team The Finance Platform & Technology team builds and scales the systems and data architecture that power OpenAI’s core financial operations. We enable business agility, compliance, and operational excellence across procure-to-pay, quote-to-cash, supply chain, financial planning, and asset management. We partner with Procurement, Accounting, Tax, Legal, Security, Data, and Engineering to modernize workflows through thoughtful platform design, reliable integrations, scalable automation, and trusted data. About the Role As a Business Systems Lead for Procure-to-Pay, you will be a hands-on engineer who designs, builds, and operates the integrations and first-party applications that power OpenAI’s procurement workflows. You will translate business needs into secure, scalable software, APIs, data flows, and automation across Oracle Fusion, Zip, and connected platforms. You will build the future of buying at OpenAI using OpenAI’s own technology, from guided intake and approval experiences to supplier onboarding, purchasing, receiving, invoicing, and downstream financial data flows. You will own the technical roadmap and support model for these capabilities, improving today’s platforms while deciding where to integrate, configure, or build as OpenAI scales. Your core strength will be software and integration engineering. You will personally write code, troubleshoot cross-system failures, and take solutions through testing, deployment, and production support. You will also make targeted functional configurations in procurement platforms and partner with functional specialists on deeper process and module design. 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 operate integrations across Oracle Fusion, Zip, and connected systems using APIs, events, messaging, and batch interfaces where appropriate. Build first-party