Senior AI Engineer, Agents and Developer Workflows

NVIDIA NVIDIA · Semiconductors · Beijing, China +1

Senior AI Engineer role focused on developing and deploying AI agents and LLM-based solutions to automate software engineering workflows within NVIDIA. The role involves creating tools to improve developer efficiency, accelerate feedback loops, and enhance release reliability, with a focus on predictive modeling for risk identification and leveraging RAG and fine-tuning techniques.

What you'd actually do

  1. Develop and implement solutions throughout software development lifecycles to improve developer efficiency, accelerate feedback loops, and boost release reliability
  2. Experience designing, developing, and deploying AI agents to automate software development workflows and processes.
  3. 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).
  4. Build and deploy predictive models to identify high-risk commits, forecast potential build failures, and flag changes that have a high probability of failures.
  5. Research emerging AI technologies and engineering best practices to continuously evolve our development ecosystem and maintain a competitive edge.

Skills

Required

  • Python
  • Java
  • Go
  • SQL
  • NoSQL
  • React
  • Angular
  • Jenkins
  • Gitlab CI
  • Packer
  • Terraform
  • Artifactory
  • Ansible
  • Chef
  • CI/CD
  • Microservice architecture
  • REST APIs

Nice to have

  • MS or equivalent experience in EE/CS
  • MySQL
  • MongoDB
  • Elasticsearch
  • RAG
  • fine-tuning LLMs
  • large-scale, service-oriented software projects
  • distributed systems

What the JD emphasized

  • 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.
  • 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.

Other signals

  • 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.
  • Build and deploy predictive models to identify high-risk commits, forecast potential build failures, and flag changes that have a high probability of failures.