Senior AI Engineer, Agents and Developer Workflows at NVIDIA

Beijing, Beijing, China -

Full Time

Start Date

Immediate

Expiry Date

07 Aug, 26

Salary

0.0

Posted On

09 May, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Large Language Models, Agentic AI, Python, Java, Go, SQL, NoSQL, React, Angular, CI/CD, Distributed Systems, Microservice Architecture, REST APIs, RAG, Fine-tuning LLMs, Machine Learning

Industry

Computer Hardware Manufacturing

Description

Today, NVIDIA is tapping into the unlimited potential of AI to define the next era of computing! An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, encouraging environment where everyone is inspired to do their best work. Come join the team and see how we can make a lasting impact on the world. NVIDIA is hiring senior software engineers in its Infrastructure, Planning and Process Team (IPP), to accelerate AI adoption across various engineering workflows within the company. IPP is a global organization within NVIDIA. The group works with various other teams within NVIDIA such as Graphics Processors, Mobile Processors, Deep Learning, Artificial Intelligence and Driverless Cars to cater to their infrastructure and software development workflow needs. As a senior engineer on AI Workflow, you will create and establish tools and software solutions that leverage Large Language Models and agentic AI to automate end to end software engineering workflows and enhance the productivity of engineers across NVIDIA. What you’ll be doing: Develop and implement solutions throughout software development lifecycles to improve developer efficiency, accelerate feedback loops, and boost release reliability Experience designing, developing, and deploying AI agents to automate software development workflows and processes. Continuously measure and report on the impact of AI interventions, showing progress in metrics such as cycle time, change failure rate, and mean time to recovery (MTTR). Build and deploy predictive models to identify high-risk commits, forecast potential build failures, and flag changes that have a high probability of failures. Research emerging AI technologies and engineering best practices to continuously evolve our development ecosystem and maintain a competitive edge. What we need to see: BE (MS preferred) or equivalent experience in EE/CS with 10+ years of work experience. Deep practical knowledge of Large Language Models (LLMs), Machine Learning (ML), and Agent development Strong background in implementing AI solutions to solve real-world software engineering problems. Hands-on experience on Python/Java/Go with extensive python scripting experience. Experience in working with SQL/NoSQL database systems such as MySQL, MongoDB or Elasticsearch. Full-stack, end-to-end development expertise, with proficiency in building and integrating solutions from the front-end (e.g., React, Angular) to the back-end (Python, Go, Java) and managing data infrastructure (SQL/NoSQL). Experience with tools for CI/CD setup such as Jenkins, Gitlab CI, Packer, Terraform, Artifactory, Ansible, Chef or similar tools. Good understanding of distributed systems, understanding of microservice architecture and REST APIs. Ability to effectively work across organizational boundaries to enhance alignment and productivity between teams. Ways to stand out from the crowd: Proven expertise in applied AI, particularly using Retrieval-Augmented Generation (RAG) and fine-tuning LLMs on enterprise data to solve complex software engineering challenges. Experience delivering large-scale, service-oriented software projects under real-time constraints, demonstrating an understanding of the complex development environments this role will optimize. Expertise in leveraging large language models (LLMs) and Agentic AI to automate complex workflows, with knowledge of retrieval-augmented generation(RAG) and fine-tuning LLMs on enterprise data. We have some of the most forward-thinking and versatile people in the world working for us and, due to unprecedented growth, our best-in-class engineering teams are rapidly growing. We are building a team that will truly change the world. If you are passionate about new technologies, care about software quality, and want to be part of the future of transportation and AI, we would love for you to join us. NVIDIA pioneered accelerated computing. Today, our AI infrastructure powers global intelligence, transforming every industry. Learn more about NVIDIA.

Responsibilities

Develop and implement AI agents and software solutions using LLMs to automate end-to-end software engineering workflows. Measure the impact of AI interventions on developer productivity and build predictive models to identify high-risk code changes.