Role at a glance
- Salary
- $168K – $310.5K/yr
- Location
- Santa Clara, California, United States
- Work arrangement
- Hybrid
- Employment
- Full-time
- Experience
- 6+ years of experience building production-grade software systems.
- Education
- BS/MS in Computer Science, Computer Engineering, Electrical Engineering, or related field (or equivalent experience)
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Role Summary
The Applied AI Engineer will work with NVIDIA's SOC Design team and its execution and methodology teams to build AI-powered tools, agents, and automation for SOC integration workflows. The role focuses on reducing cycle time and manual effort through RAG-based knowledge systems, LLM assistants, agentic development tools, and reliable integrations with internal design infrastructure.
What You'll Do
- Develop LLM-powered tools for design review summarization, signoff status aggregation, integration checklist enforcement, CI/CD pipeline...
- 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.
- Own AI system reliability and evaluation through logging, tracing, prompt regression testing, and output validation frameworks.
- Collaborate with SOCD execution and methodology teams to scope problems, validate solutions, and define productivity metrics for...
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Build and deploy production-grade AI/LLM-powered applications, agents, automation workflows, and services using Python, LLM application frameworks, RAG architectures, and software engineering practices.
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
- Experience shipping AI/LLM-powered applications, agents, or automation workflows into production environments
- Strong Python skills
- Experience building LLM-powered agents or agentic workflows
- Hands-on experience with LLM application frameworks such as LangChain or LlamaIndex, or equivalent
- Experience with RAG architectures, including chunking, embedding models, vector databases, and retrieval design
- Software engineering fundamentals including system design, API design, testing, CI/CD, code quality, observability, security, databases,...
Preferred
- Fine-tuning or domain-specific prompt engineering
- Experience with MCP (Model Context Protocol) or similar tool-calling standards
- Multi-agent orchestration frameworks
- Knowledge of ASIC development and SOC integration
- Experience building lightweight internal tools or full-stack applications, including React/TypeScript frontends with FastAPI backends
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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.About the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.