Technical Architect in United States

About the Team OpenAI’s Hardware organization develops system and infrastructure solutions optimized for advanced AI workloads. We collaborate across research, software, and external hardware partners to design and deploy next-generation AI systems at scale. Our team works closely with silicon vendors and system partners to evaluate emerging technologies, validate performance characteristics, and ensure that hardware capabilities translate effectively to real-world AI workloads. About the Role We are seeking a 3P Hardware Architecture Expert with deep expertise in GPU and accelerator architectures to engage directly with silicon vendors and guide hardware decisions for AI infrastructure. In this role, you will evaluate architectural tradeoffs across compute, memory, and interconnect systems, translating vendor specifications into real-world workload impact. You will play a critical role in early silicon evaluation, benchmarking, and performance validation, helping ensure that next-generation hardware meets the needs of our workloads. This role is highly hands-on and requires both deep technical understanding and the ability to engage at a high level with partners such as NVIDIA and AMD on architectural direction and design tradeoffs. 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. Key Responsibilities Engage deeply with silicon vendors (e.g NVIDIA & AMD) on GPU and accelerator architecture tradeoffs. Analyze and interpret performance, power, and efficiency characteristics of next-generation hardware. Translate vendor specifications into expected real-world performance for AI workloads. Evaluate architectural aspects including: compute throughput and utilization memory systems (HBM, cache hierarchies, bandwidth constraints) data types and precision tradeoffs (FP16, BF16, FP8, etc.) interconnect and scaling behavior. Run benchmarks and profiling to validate hardware performance a

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. Our Solution Engineering organization is seeking an AI Specialist who can provide hands-on expertise and support while working with technical decision makers and data scientists to design and architect AI solutions built on the Snowflake AI Data Cloud. This is a strategic role that works closely with cross-functional teams, including product, engineering, and the broader field organization to ensure successful execution and customer adoption of Snowflake’s AI & ML solutions. IN THIS ROLE YOU WILL GET TO: Be the technical expert in the room that positions Snowflake’s AI and ML features and value to technical stakeholders at Snowflake’s customers across the Americas. Partner with Snowflake account team teams and customer champions to scope and drive POCs to success and technical wins that prove the value of Snowflake’s capabilities, including executive readouts and business value cases. Collaborate with Snowflake’s product and engineering teams to influence Snowflake’s AI and ML roadmaps based on customer feedback. Publish content that helps the team and company scale beyond your individual efforts, like blog posts, presentations at conferences, or technical collateral like notebooks and demos. Influence, tailor and maintain Sales Engineering AI and ML selling assets, inc

At Freddie Mac, our mission of Making Home Possible is what motivates us, and it’s at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose. Position Overview: We need a highly innovative Technical Lead! How confident are you that you can build sophisticated analytic systems? If you believe you could contribute to the development of innovative principles and ideas in a matrixed environment, please keep reading as we are seeking an individual contributor who has experience with Java and Python and can lead and nurture an inspiring environment in our Virginia office. Our Impact: The Investments and Capital Markets (I&CM) division is looking for a capable technology lead for its trading and analytics development team. This could be you! To thrive in this division, you must have a comprehensive understanding of system implementation and design, experience working in capital markets, and be enthusiastic about leading development of new paradigms in software system architecture. Your Impact: As a Trading Analytics Development Tech Lead, you will develop and maintain software using Java and Python tech stack that adheres to software engineering best practices. You will influence technical decisions, mentor developers, resolve engineering blockers, and partner with engineering managers to help teams deliver secure, reliable, and maintainable solutions. You will provide hands-on directions for full-stack applications, APIs, microservices, and integration services while reinforcing engineering discipline across design, development, testing, deployment, observability, and production readiness. Partner closely with Product Owners, engineering managers, architecture, business stakeholders, and cross-functional tec

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 Product Management - Technical About Mastercard Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships, and passion, our innovations help individuals, financial institutions, governments, and businesses realize their greatest potential. Role Summary We are looking for a **Principal Product Manager – Technical** to lead product strategy and execution for **global, real‑time switching and authorization platforms**.In this role, you will own the vision, roadmap, and delivery of **mission‑critical transaction processing capabilities** that operate at massive scale with strict requirements for availability, latency, resiliency, and correctness. You will work closely with engineering, architecture, operations, and business leaders to deliver platforms that support billions of transactions and enable reliable, secure payment experiences worldwide. This is a **senior individual contributor role** with broad influence across teams, regions, and portfolios. What You’ll Do Product Strategy & Vision* Define and own the long‑term product vision and strategy for switching and authori

NVIDIA is looking for a hands-on Solutions Architect Manager to lead a team of GPU, networking & software solution architects and engineers. Do you want to build and lead a group that designs, debugs, and deploys new AI hardware and software technologies into production in customer data centers? As part of the NVIDIA SA organization, you will drive people and technical leadership for end-to-end solutions deployments at some of NVIDIA's most strategic technology customers, while directly contributing to designs and deep-dive debugging and shaping our product roadmap with customer feedback. What you will be doing: Recruit & manage a team of solutions architects, system/network and software engineers focused on large-scale GPU and AI networking deployments. Set priorities, allocate resources, mentor, and ensure high-quality customer delivery across multiple concurrent projects - while remaining directly involved in key technical reviews, design decisions, and critical debug efforts. Provide deep subject-matter expertise in advanced GPU and network systems and serve as the senior technical point of contact for strategic customers. Personally lead and guide complex compute/network configuration and performance debugging, working side-by-side with your team to deliver performant, reliable clusters. Guide your team as they lead network / compute / software architecture discussions, and support server, network, and cluster bring-up, including on-site data center work where needed. Systematically collect and synthesize customer-specific requirements across your portfolio. Partner with GPU/Network Systems Engineering, Product Management, and Sales to influence roadmap priorities and packaging of reference designs and solutions. Demonstrate SME in advanced GPU & network systems and be a trusted technical advisor to NVIDIA's strategic customers. Bring customer-sp

NVIDIA DGX Cloud is an AI Factory designed to power the next generation of AI and industrial-scale breakthroughs. As the Distinguished Engineer for Security Architecture, within our Security Engineering organization, you will set the security design bar for an AI factory of hundreds of thousands of GPUs, and then build against it alongside the teams. This is the founding architecture seat in a new organization. Security Engineering is a new organization at DGX Cloud, accountable for the security outcome of the platform, and this is the architecture function inside it. You will define the security design standard for DGX Cloud, a bar that sits above the company floor, and hold it from inside the teams doing the building. Security here is fleet horizontal and stack vertical, so your scope runs from the hardware root of trust and the hardened baseline, through tenancy and GPU workload isolation, to the services and APIs built on top, across every DGX Cloud engineering organization. A small team of Principal Engineers will report to you and hold the bar at domain depth. This is still a hands-on seat, and you stay in the design with them. You will also serve as DGX Cloud's technical interface into NVIDIA's central security organization. There is no architecture review board here and no approval queue; the bar holds because the strongest security engineers in the room helped set it and helped ship it. What You Will Be Doing: Set the DGX Cloud Security Bar: Own the security design standard across DGX Cloud (tenancy, GPU workloads, identity, supply chain, and isolation) and make it concrete. Reference architectures, golden paths, and requirements engineers can actually build against, not a policy library. Hold the Bar by Building: Embed with engineering teams on real work: join the design, learn the code, help ship the thing rather than grade it afterward.

About the Team The GTM Enablement team helps OpenAI’s customer-facing organizations turn rapidly evolving AI capabilities into consistent, high-quality customer outcomes. We build the onboarding, learning experiences, playbooks, and knowledge systems that help teams develop technical depth, stay current, and confidently guide customers through successful AI adoption. About the Role We’re hiring a Field Enablement Lead, Technical Success to design and scale enablement for our rapidly growing technical customer-facing teams. You will own programs spanning onboarding, continuous skill development, technical pitches and demos, and subject-matter-expert knowledge sharing. Working closely with Technical Success leaders, Product Enablement, and technical SMEs, you will turn complex product knowledge and field experience into practical systems that improve readiness, consistency, and the quality of customer interactions and deployments. In this role, you will: Design, implement, and scale comprehensive enablement programs aligned to Technical Success onboarding, role-based skill development, and ongoing readiness needs. Redefine and operate the Subject Matter Expert (SME) program, creating clear pathways for technical experts to share knowledge and raise technical depth and consistency across GTM. Own and proactively maintain a versioned repository of technical pitches, demos, playbooks, and launch-ready assets. Partner with Technical Success leadership, Product Enablement, and product SMEs to identify skill gaps and deliver targeted learning interventions. Capture, vet, organize, and make field- and SME-generated technical content easy to discover, trust, and reuse. You might thrive in this role if you have: 5+ years of experience in technical enablement, solutions engineering, solutions architecture, technical success, or a related role. A proven track record of designing and scaling technical enablement programs in high-growth SaaS or technology environments. Exceptional

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: At Modal, we sell cloud services atop which our customers run their critical production systems. As a rapidly growing new cloud infrastructure company, we seek to improve our reliability dramatically while scaling the size of our platform, customer base, and our team. This role is for people who are deep systems thinkers, love stacking nines, and thrive from making others move faster at scale. Responsibilities include: Identifying architectural changes to improve reliability and performance. Fostering a culture of reliability across Modal’s engineering organization. Defining and implementing operational processes such as deployments, upgrades, etc. Operating systems like Kubernetes, Postgres, Redis, etc. Participating in on-call rotations, and responding to production incidents. Requirements: 5+ years of experience writing high-quality production code. 2+ years of

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for strong engineers with experience in making ML systems performant at scale. If you are interested in contributing to open-source projects and Modal’s container runtime to push language and diffusion models towards higher throughput and lower latency, we’d love to hear from you! Requirements: 5+ years of experience writing high-quality, high-performance code. Experience working with torch, high-level ML frameworks, and inference engines (vLLM or TensorRT). Familiarity with Nvidia GPU architecture and CUDA. Experience with ML performance engineering (tell us a story about boosting GPU performance — debugging SM occupancy issues, rewriting an algorithm to be compute-bound, eliminating host overhead, etc). Nice-to-have: familiarity with low-level operating system foundations (Linux kernel, file systems, containers, etc).

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Our team is a fast-growing group of researchers and engineers focused on building reliable ML systems and pushing the boundaries of LLM inference efficiency. We develop techniques that improve how models execute in production, driving lower latency, higher throughput, and consistent quality across diverse workloads. As an engineer on this team, you’ll work across the inference stack to improve core performance metrics by diving deep into model execution, identifying bottlenecks, and developing innovative optimizations. You’ll collaborate closely with modeling and systems teams to experiment, measure, and ship improvements that meaningfully accelerate inference. As the team evolves, you’ll have opportunities to build expertise in advanced performance techniques, including GPU/CUDA optimizations, kernel-level improvements, and model execution strategies for MoE and large-scale architectures. Please Note: We have offices in Toronto, Montreal, San Francisco, New York, Paris, Seoul and London. We embrace a remote-friendly environment, and as part of this approach, we strategically distribute teams based on interests, e

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Are you energized by leading the design of high-performance, scalable and reliable machine learning systems? Do you want to set technical direction and help shape the next generation of AI platforms powering advanced NLP applications? We are looking for a Lead Member of Technical Staff to join the Model Serving team at Cohere. The team is responsible for developing, deploying, and operating the AI platform delivering Cohere's large language models through easy to use API endpoints. In this role, you will provide technical leadership across multiple teams, driving the architecture and strategy for deploying optimized NLP models to production in low latency, high throughput, and high availability environments. You will serve as a key point of contact for customers, leading the design of customized deployments to meet their specific needs, and mentoring engineers to raise the technical bar across the team. You may be a good fit if you have: 8+ years of engineering experience running production infrastructure at a large scale, with a track record of technical leadership Demonstrated experience leading the architecture

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. Data Engineering - Applied Field Engineer- CA- Menlo Park- Remote 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. Our Solution Engineering organization is seeking a Data Engineering Specialist to join our Applied Field Engineering team who can provide technical leadership in working with both technical and business executives in the design and architecture of the Snowflake Cloud Data Platform as a critical component of their enterprise data architecture and overall ecosystem. In this role you will work directly with the sales team to understand the needs of our customers, strategize on how to navigate winning sales cycles, provide compelling value-based demonstrations, support enterprise Proof of Concepts, and ultimately close business. You will leverage your expertise, best practices and reference architectures highlighting Snowflake’s Data Platform capabilities across data ingestion, transformation, and lakehouse workloads. You are equally comfortable in both a business and technical context, interacting with executives and talking shop with tec

Who Are We? Postman is the world’s leading API platform, used by more than 45 million+ developers and 500,000 organizations, including 98% of the Fortune 500. Postman is helping developers and professionals across the globe build the API-first world by simplifying each step of the API lifecycle and streamlining collaboration—enabling users to create better APIs, faster. The company is headquartered in San Francisco and has offices in Boston, New York, Austin, Tokyo, London, and Bangalore - where Postman was founded. Postman is privately held, with funding from Battery Ventures, BOND, Coatue, CRV, Insight Partners, and Nexus Venture Partners. Learn more at postman.com or connect with Postman on X via @getpostman. P.S: We highly recommend reading The "API-First World" graphic novel to understand the bigger picture and our vision at Postman. The Opportunity As a Member of Technical Staff and AI Agent Development Lead, you will lead the design, development, and deployment of next-generation AI agents that interact with users and complex environments. You will drive the architecture and implementation of scalable, reliable AI systems, working closely with research, product and engineering teams to build safe, interpretable, and performant AI technology. What You’ll Do Lead a cross-functional engineering team focused on AI agent development, from conceptual design to production deployment. Design and implement AI agent architectures leveraging state-of-the-art language models and associated technologies. Collaborate with research scientists on scalable experiments and productize research innovations. Drive the development of agent capabilities including dialogue management, decision making, and autonomy. Ensure AI safety and alignment principles are integrated throughout the agent lifecycle. Mentor and grow technical staff, fostering an environment of collaboration and innovation. Evaluate new tools, frameworks, and methodologies to enhance AI agent capabilities. Partner

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore fosters continuous learning and innovation. Job Summary Reporting into the Systems Engineering organisation, the Distinguished Engineer, End-to-End Security Architect will define and lead the security architecture for Graphcore’s inference service platform. This role is responsible for establishing a comprehensive security strategy spanning platform, infrastructure, networking, service operations, customer assurance, and compliance readiness. Working across multiple engineering and operational functions, the successful candidate will provide technical leadership, drive security requirements, and ensure the platform delivers robust protection, resilience, and trust for customers. The Team You will work closely with teams across security architecture, infrastructure engineering, networking, site reliability engineering, platform software, firmware, data centre operations, compliance, legal, customer engineering, and customer security. The team collaborates across the business to deliver secure, reliable, and scalable AI infrastructure and services while supporting customer assurance, regulatory requirements, and operational excellence. Responsibilities and Duties Own the end-to-end security a

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 As Manager (Player & Coach) of the Solution Architect team, you will lead and mentor a team of Solution Architects who will partner closely with Sales and customers to translate business needs into technical solutions, run technical discovery, and guide repeatable deployments and proofs of value for customers. Applying both hands-on technical ownership and managerial leadership, you will guide your team through the processes of owning discovery calls, demos, technical scoping and driving POC’s through to execution as well as designing, deploying, and managing high performance, low latency AI applications on Baseten’s platform. You will also partner with product, infrastructure, and other customer engineering teams to ensure that large language models (LLMs) and other generative AI systems deliver best-in-class performance, reliability, and cost efficiency in production environments. EXAMPLE INITIATIVES Take a look at these blog posts written by members of our Forward Deployed Engineering team: Forward Deployed Engineering on the frontier of AI The fastest, most accurate Whisper transcription Deploy production-ready model servers from Docker images Deploy custom ComfyUI workflows as APIs RESPONSIBILITIES Leadership Lead, mentor, and grow a team of Solution Architects, providing guidance on technical direction, project execution, and professional development. Set clear goals and ensure timely, high-quality d