The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits. NVIDIA is seeking a hands-on, action-oriented Senior Solutions Architect to join our team, focused on the technical execution across engineering, product, and sales teams and support to achieve Hyperscaler-scale deployment for our groundbreaking data center products.
The ideal candidate has experience managing global infrastructure projects/programs, navigating inventory or supply chain management systems and understanding basic network/server/power infrastructure to perform data entry and changes for landing complex rack services with different placement rules. As a Technical Infrastructure Program Manager within this team focused on global data center inventory and power topology accuracy, you will be the gatekeeper (configure, update and maintain) for all global infrastructure data for core data centers pertaining to rack floor plan layout.
Seattle, Washington30+ days ago
Technical Vendor Management: Own vendor relationships with partners including Optimizely and Quantum Metric, defining platform roadmap requirements, feature prioritization, integration needs, and performance expectations.
Product execution and delivery: Write user stories, acceptance criteria, and technical requirements for platform features, tooling improvements, vendor integrations, and infrastructure upgrades.
li>Create simple abstractions for complex workloads: Define product experiences that make it easy for developers to run long-lived agents, fork sessions, resume work, attach tools, manage credentials, execute code safely, and observe agent behavior. Work backwards from agent-native customers: Partner directly with companies building coding agents, productivity agents, workflow agents, and custom AI systems to understand the infrastructure they need to move from prototype to production.
li>Drive technical strategy: Partner with technical leads, researchers, and legal to set direction for privacy infrastructure across training, inference, and product surfaces: data governance and policy enforcement, deletion and retention at scale, encryption and key management, audit and access transparency, and ML-based PII detection and redaction. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Additionally, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the Company's legal duty to furnish information. As Accenture continues to grow, you may see a variety of new career opportunities, and depending on the role and location you may be directed to apply through Accenture Infrastructure and Capital Projects LLP or one of our other legal entities - Accenture Infrastructure and Capital Projects, LLC or Accenture Infrastructure and Capital Projects Inc., with benefits varying by country and role, so please check with your recruiter for details.
li>Define and drive requirements for serviceability, deployability, and maintainability of new products in the data center environment while acting as the primary liaison between engineering design teams and data center operations teams. Understand product designs, assess risks, and contribute to technical problem-solving including resolving hardware/software issues during new product introduction phases.
li>Define and drive requirements for serviceability, deployability, and maintainability of new products in the data center environment while acting as the primary liaison between engineering design teams and data center operations teams. Understand product designs, assess risks, and contribute to technical problem-solving including resolving hardware/software issues during new product introduction phases.
From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more. SWE teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day.