Principal Cybersecurity Architect jobs at Nvidia

What you’ll be doing:

• Working with tech giants to develop and demonstrate solutions based on NVIDIA’s groundbreaking software and hardware technologies.

• Partnering with Sales Account Managers and Developer Relations Managers to identify and secure business opportunities for NVIDIA products and solutions.

• Serving as the main technical point of contact for customers engaged in the development of intricate AI infrastructure, while also offering support in understanding performance aspects related to tasks like large scale LLM training and inference.

• Conducting regular technical customer meetings for project/product details, feature discussions, introductions to new technologies, performance advice, and debugging sessions.

• Collaborating with customers to build Proof of Concepts (PoCs) for solutions to address critical business needs and support cloud service integration for NVIDIA technology on hyperscalers.

• Analyzing and developing solutions for customer performance issues for both AI and systems performance.

What we need to see:

• BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or other Engineering fields or equivalent experience.

• 4+ years of engineering(performance/system/solution)experience.

• Hands-on experience building performance benchmarks for data center systems, including large scale AI training and inference.

• Understanding of systems architecture including AI accelerators and networking as it relates to the performance of an overall application.

• Effective engineering program management with the capability of balancing multiple tasks.

• Ability to communicate ideas clearly through documents, presentations, and in external customer-facing environments.

Ways to stand out from the crowd:

• Hands-on experience with Deep Learning frameworks (PyTorch, JAX, etc.), compilers (Triton, XLA, etc.), and NVIDIA libraries (TRTLLM, TensorRT, Nemo, NCCL, RAPIDS, etc.).

• Familiarity with deep learning architectures and the latest LLM developments.

• Background with NVIDIA hardware and software, performance tuning, and error diagnostics.

• Hands-on experience with GPU systems in general including but not limited to performance testing, performance tuning, and benchmarking.

• Experience deploying solutions in cloud environments including AWS, GCP, Azure, or OCI as well as knowledge of DevOps/MLOps technologies such as Docker/containers, Kubernetes, data center deployments, etc. Command line proficiency.

What You'll Be Doing:

• Working as a key member of our cloud solutions team, you will be the go-to technical expert on NVIDIA's products, helping our clients architect and optimize GPU solutions for AI services.

• Collaborating directly with engineering teams to secure design wins, address challenges, usher projects into production, and offer support through the project's lifecycle.

• Acting as a trusted advisor to our clients, while developing reference architectures and best practices for running Microsoft AI workloads on NVIDIA infrastructure.

What We Need To See:

• 4+ years of experience in cloud computing and/or large-scale AI systems.

• A BS in EE, CS, Math, or Physics, or equivalent experience.

• A proven understanding of cloud computing and large-scale computing systems.

• Proficiency in Python, C, or C++ and experience with AI frameworks like Pytorch or TensorFlow.

• Passion for machine learning and AI, and the drive to continually learn and apply new technologies.

• Excellent interpersonal skills, including the ability to explain complex technical topics to non-experts.

Ways To Stand Out From The Crowd:

• Recent projects or contributions (for example, on GitHub) related to large language models and transformer architectures.

• Knowledge of Azure cloud and AzureML services.

• Experience with CUDA programming and optimization.

• Familiarity with NVIDIA networking technologies such as Infiniband.

• Proficiency in Linux, Windows Subsystem for Linux, and Windows.

What you’ll be doing:

• Collaborating with business development in guiding the customer through the solution adoption process for our Metropolis, Isaac and IGX AI SW platforms, GPU Computing and IGX/Jetson, being responsible for the technical relationship and assisting customers in building creative solutions based on NVIDIA

• Be an industry leader with vision on integrating NVIDIA technology into intelligent machines’ architectures

• You will engage with customers to develop a keen understanding of their goals, vision and plans, as well as technical needs – and help to define and deliver high-value solutions that meet these needs

• Train customers on the adoption of our AI platforms, develop and optimize proof of concepts using the Nvidia robotics and Metropolis platforms as well as the Jetson/IGX SDKs

• Establish positive relationships and communication channels with internal teams

What we need to see:

• BS or MS in Electrical Engineering or Computer Science or equivalent experience

• 8+ years of work-related experience in a high-tech electronics industry in a similar role as a systems or solution architect

• AI practitioner experience

• C, C++, and Python coding

• Strong time-management and organization skills for coordinating multiple initiatives, priorities, and implementations of new technology and products into very complex projects

Ways to stand out from the crowd:

• NVIDIA GPU development experience

• Experience with Omniverse, ISAAC and Metropolis

• Experience with generative AI on Jetson or IGX, RIVA, VSS

What you’ll be doing:

• Pre-silicon Power Estimation: Model and estimate CPU power at C-model, RTL, and netlist stages using industry-standard tools.

• Power Optimization: Identify inefficiencies and drive design improvements in collaboration with architects, RTL designers, and PD engineers.

• Test Development: Create targeted power characterization tests (e.g., peak power, di/dt stress patterns) for both simulation and silicon.

• Silicon Validation: Measure CPU power and performance in the lab; correlate silicon results with pre-silicon estimates to refine models.

• Cross-functional Collaboration: Partner with multiple engineering disciplines to achieve optimal power efficiency without compromising performance.

What we need to see:

• BS/MS in EE, CE, or CS or equivalent experience.

• 3+ years of experience working in ASIC power measurement and optimization.

• Strong understanding of leakage and dynamic power in VLSI circuits

• Experience with RTL and netlist power analysis tools such as Power Artist, PrimeTime PX, or equivalent.

• Familiarity with CPU microarchitecture (CPU pipeline design, out-of-order execution, cache hierarchy, branch prediction) and understanding of microarchitectural power model.

Ways to stand out from the crowd:

• Proficiency in Python for automation and data analysis.

• Experience with DVFS, clock gating, power gating, and multi-voltage domain design.

• Knowledge of lab instrumentation for power measurement.

• Strong communication skills for cross-team technical discussions.

What you’ll be doing:

• Introduce and integrate NVIDIA networking products with Hyperscalers

• Build customers’ trust and understand their unique needs

• Address sophisticated and obvious customer issues alongside engineering and support teams

• Conduct technical meetings for project/product details, feature discussions, and debugging sessions

• Partner with Sales and Product teams to identify and secure business opportunities, analyze network requirements, and designs next-gen AI platforms

• Develop Proof of Concept (PoC) solutions for critical business needs

• Prepare and deliver technical presentations and workshops to customers

What we need to see:

• Bachelor’s degree or higher in Electrical/Computer Engineering or related field (or equivalent experience)

• 12+ years of Solutions Engineering or similar engineering experience

• Passion to enhance customer experience

• Proficiency in networking fundamentals, including NICs, server systems, data center architecture, switching, routing, networking protocols, and data center architecture

• Comprehensive knowledge of computer system architecture, Linux, PCIe devices as it relates to networking performance

• Experience in configuring, testing, and troubleshooting in networking environments

• Ability to work independently and manage multiple priorities

• Excellent communication skills to act as a trusted advisor to customers

Ways to stand out from the crowd:

• Experience working with custom network OS (such as SONiC, FBOSS, or similar)

• Experience working with or calling on Cloud Service Providers (e.g., Meta)

• Exemplify a unique combination of strong interpersonal skills and technical proficiency

• Showcase in-depth knowledge of RDMA, including performance testing and AI benchmarking

• Background with NVIDIA hardware and software

What you’ll be doing:

• Agentic Workflow Design: Build autonomous agents that handle the full TPRM lifecycle.

• Employ Generative AI Technology like embeddings, RAG, or LLM agents for summarizing vendor responses.

• Continuous Monitoring Automation: Build event-driven integrations (webhooks, serverless functions) to react to vendor risk score changes or asset discovery events.

• NLP and ETL Automation: Use Natural Language Processing (NLP) for extracting structured data from vendor documents and maintain pipelines for ingesting and correlating vendor risk data, findings, and compliance metrics.

• Integration Architecture: Design modular, API-based pipelines connecting TPRM tooling (LogicGate/OneTrust) with Databricks, Jira, and data warehouses.

• Domain Alignment: Apply deep understanding of the TPRM Lifecycle (onboarding, risk tiering, assessment, remediation) and ensure security relevance based on frameworks such as NIST CSF 2.0, ISO 27001, SOC 2, and CMMC mappings.

• Risk Modeling: Integrate knowledge of Risk Scoring Models (e.g., BitSight scores) into inherent and residual risk calculations.

What we need to see:

• API Engineering: Experience integrating data from security and GRC systems such as BitSight, LogicGate, ServiceNow, or Jira.

• Workflow Automation Tools: Understanding of orchestration and automation systems such as Tines, n8n, Cortex XSOAR for prototypes).

• Data Modeling & Pipelines: Ability to design and maintain data models for vendor metadata, risk scores, and control test results.

• Proficient in using tools like Cursor, Claude, Gemini, or similar frameworks to develop agentic automations for data analysis and workflow execution.

• Observability & Metrics: Ability to implement logging, monitoring, and metrics dashboards (e.g., PowerBI) for TPRM automation health.

• 8+ years of proven experience in cybersecurity with a focus on automation, security engineering, or architecture.

• Communication & System Thinking: Strong cross-functional communication. System thinking to translate policy/compliance goals into technical automation design.

• Leadership: Innovation mindset: Ability to propose and prototype emerging AI approaches responsibly; Excellent Documentation & Knowledge-sharing skills of automation architecture, runbooks, and control mappings.

• Minimum bachelor’s degree or equivalent experience in a technology or relevant scientific field required.

Ways to stand out from the crowd:

• Certifications in one or more of the following areas: CIPP, CISSP, CISA, CISM, CRISC.

• Proficiency in using third-party risk management platforms such as OneTrust, RSA Archer, or similar tools.

• Hands-on experience with developing and maintaining metrics dashboards for Cybersecurity programs.

• Demonstrated ability to manage and mitigate risks associated with a large and diverse portfolio of third-party vendors.

What you'll be doing:

• Create products to help researchers and production model builders

• Develop product strategy, roadmaps, and go-to-market plans

• Collaborate with internal and external customers to build product-based roadmaps for training/post training software

• Work with leadership to align with and drive company strategy

What we need to see:

• Experience with training/post training and optimization software (ex. PyTorch distributed, torchtitan, VeRL, Nemo Framework, etc.)

• Demonstrable knowledge of GenAI or machine learning concepts, particularly around model training, performance optimization, and software development and delivery

• Experience with large scale distributed systems

• BS or MS degree in Computer Science, Computer Engineering, or similar experience (or equivalent experience)

• 15+ years of technical product management, or similar, experience at a technology company

• Strong communication and interpersonal skills

Ways to Stand Out from the crowd:

• Experience leading GenAI/RecSys research to production at scale

• Working on Open Source & Github-first developer products with deep customer interactions

• Knowledge of GPU architecture, HW/SW co-design, and performance profiling