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NVIDIA

Senior SOCD Applied AI Engineer

  • Hybrid
  • 6+ years

Salary

$168,000 - 264,500/ year

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Description

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.

Responsibilities

  • Applications for this job will be accepted at least until September 6, 2026.
  • 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.

Where you’d work

Part of the week in the office

You can work from

  • United States

About the company

NVIDIA

Office in United States

Also hiring in Munich, Germany, France, Bristol, United Kingdom and 13 more places

273 of their 660 open roles are remote

Your chances

Worth a look before you spend an evening tailoring a CV for it.

  • 21 checks run
  • 2 red flags

Still hiring?

14 checks

1 red flag

How crowded?

7 checks

1 red flag

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  • Your field
  • Level
  • Stack
  • Work model
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  • Must-haves
Details13 facts · Role, Location, Compensation, Employment
Tech stack
  • React
  • TypeScript
  • Python
  • CI/CD
  • LLMs
  • RAG
  • LangChain
  • Vector databases
Seniority
Senior
Type
Full-time
Equity
Equity offered
Specialty
ML
Region
United States
Show 7 more factsShow less

Role

Category
Data & Analytics
Specialty
ML
Seniority
Senior
Experience
6+ years
Tech stack
  • React
  • TypeScript
  • Python
  • CI/CD
  • LLMs
  • RAG
  • LangChain
  • Vector databases

Location

Work model
Hybrid
Region
United States
Office
  • United States
Remote from
  • United States

Compensation

Salary
$168,000 - 264,500 / year
Pay period
Annual
Equity
Equity offered

Employment

Type
Full-time

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