Nvidia's SOC Design (SOCD) team is looking for an Applied AI Engineer who is passionate about eliminating bottlenecks in SOC integration workflows through intelligent automation. If you are driven to build AI-powered tools, agents, and automation solutions to dramatically reduce cycle time and manual effort, come join us.
You will be working directly with SOCD execution and methodology teams to identify areas that can be accelerated with the use of AI services, from RAG-grounded knowledge systems and LLM-powered assistants to multi-step agents that plug into the internal design infrastructure!
What you'll be doing
Develop LLM-powered tools for high-value execution tasks: design review summarization, signoff status aggregation, integration checklist enforcement, CI/CD pipeline gating, and cross-team status reporting.
Build and deploy RAG-based knowledge systems grounded in internal design documentation and execution artifacts.
Design AI-assisted coding workflows, including agent-based development tools, reusable prompt templates, and structured skills to accelerate engineering productivity.
Own reliability and evaluation of AI systems, including logging, tracing, prompt regression testing, and output validation frameworks.
Collaborate closely with SOCD execution and methodology teams to scope problems, validate solutions, and define metrics for productivity gains from deployed automation.
What we need to see
BS/MS in Computer Science, Computer Engineering, Electrical Engineering, or related field (or equivalent experience)
6+ years of experience building production-grade software systems.
Proven experience shipping AI/LLM-powered applications, agents, or automation workflows into production environments.
Strong Python skills with the ability to design, prototype and productize AI-enabled services, APIs, integrations, automation workflows, and internal tools.
Practical experience building LLM-powered agents or agentic workflows, with hands-on use of Claude Code, OpenAI Codex, Cursor, or equivalent coding agents to improve development workflows.
Hands-on experience with LLM application frameworks (LangChain, LlamaIndex, or equivalent) and RAG architectures — including chunking, embedding models, vector databases, and retrieval design.
Solid software engineering fundamentals and production mindset, including system design, API design, testing, CI/CD, code quality, observability, security, databases, containers, and distributed or event-driven systems.
Ability to identify repetitive, high-friction, or knowledge-intensive workflows and turn them into practical AI-enabled tools, automations, or assistants that improve productivity and operational efficiency.
Demonstrated end-to-end ownership of engineering solutions, from architecture and development to deployment, integration, and ongoing operations/support.
Excellent communication skills and a collaborative, proactive approach.
Ways to stand out from the crowd
Advanced AI techniques: fine-tuning or domain-specific prompt engineering (e.g., adapting models to understand RTL patterns); experience with MCP (Model Context Protocol) or similar tool-calling standards for interoperable agent ecosystems; multi-agent orchestration frameworks.
Knowledge of ASIC development and SOC integration to better understand user needs.
Experience building lightweight internal tools or full-stack applications (e.g., React/TypeScript frontends with FastAPI backends) to surface AI capabilities.
With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant people in the world working for us and, due to unprecedented growth, our teams are rapidly growing. Are you passionate about becoming a part of a best-in-class team supporting the latest in GPU and AI technology? If so, we want to hear from you.
#LI-Hybrid
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 264,500 USD for Level 4, and 196,000 USD - 310,500 USD for Level 5.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Skills Required
- BS/MS in Computer Science, Computer Engineering, Electrical Engineering, or related field (or equivalent experience)
- 6+ years of experience building production-grade software systems
- Proven experience shipping AI/LLM-powered applications, agents, or automation workflows into production environments
- Strong Python skills for designing, prototyping and productizing AI-enabled services, APIs, integrations, and automation workflows
- Practical experience building LLM-powered agents or agentic workflows (Claude Code, OpenAI Codex, Cursor, or equivalent)
- Hands-on experience with LLM application frameworks (LangChain, LlamaIndex, or equivalent) and RAG architectures, including chunking, embedding models, and vector databases
- Solid software engineering fundamentals and production mindset (system design, API design, testing, CI/CD, code quality, observability, security, databases, containers, distributed/event-driven systems)
- Ability to identify repetitive, knowledge-intensive workflows and convert them into practical AI-enabled tools and automations
- Demonstrated end-to-end ownership from architecture through deployment, integration, and operations/support
- Excellent communication skills and collaborative, proactive approach
- Experience with advanced AI techniques (fine-tuning, domain-specific prompt engineering), MCP or tool-calling standards, or multi-agent orchestration frameworks
- Knowledge of ASIC development and SOC integration
- Experience building internal tools or full-stack applications (React/TypeScript frontends with FastAPI backends)
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
