Senior Software Engineer, AI Agent Platforms

NVIDIA NVIDIA · Semiconductors · Yokneam, Israel +1

Senior Software Engineer role focused on building AI agent platforms for NVIDIA's networking architecture organization. The role involves developing AI agents to solve engineering problems, creating reliable platforms for these agents, driving AI adoption, and establishing best practices, guardrails, and evaluation methods. The goal is to multiply the output of hundreds of engineers through AI.

What you'd actually do

  1. Build AI agents that solve real engineering problems across the networking stack — and ship them to daily use.
  2. Design and build the platforms that make those agents reliable: typed tool surfaces, cloud services, and the systems behind them.
  3. Work broadly across networking architecture teams to identify high-impact AI use cases and turn them into working solutions.
  4. Drive rapid and responsible AI adoption across the organization: establish best practices, guardrails, and evaluation methods so teams embrace agentic workflows with confidence.
  5. Build evaluation pipelines that measure and improve AI-agent behavior on real production workloads.

Skills

Required

  • BSc in Computer Science or a related field, or equivalent experience.
  • 5+ years of relevant practical experience in software development, including working on a large-scale software product.
  • Advanced, demonstrable use of AI and agentic workflows in your daily engineering work well beyond standard coding assistant usage.
  • A fast learner, comfortable moving across codebases, domains, and teams.
  • A drive for end-to-end ownership and strong communication skills.

Nice to have

  • Cloud-native development experience (containers, Kubernetes, CI/CD pipelines).
  • Background in computer networking or HPC.

What the JD emphasized

  • Advanced, demonstrable use of AI and agentic workflows in your daily engineering work well beyond standard coding assistant usage.
  • guardrails
  • evaluation methods
  • agentic workflows
  • evaluation pipelines
  • AI-agent behavior

Other signals

  • Build AI agents that solve real engineering problems
  • Design and build the platforms that make those agents reliable
  • Drive rapid and responsible AI adoption across the organization
  • Build evaluation pipelines that measure and improve AI-agent behavior