Senior Software Manager, Agentic AI

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

Senior Software Manager to lead a team building agentic AI solutions for chip design workflows, involving coding agents, custom skills, and integration with enterprise systems. The role requires technical leadership in designing, developing, and deploying AI applications using LLMs and agentic systems, including model customization (fine-tuning, RL, instruction tuning) and overseeing retrieval/generation algorithms for enterprise data. Collaboration with cross-functional teams and ensuring high technical standards for evaluation, guardrails, and monitoring are key.

What you'd actually do

  1. Manage and grow a team building agentic AI solutions, including sophisticated coding agents, custom skills/tools, and their integration with enterprise production systems for chip design workflows.
  2. Provide technical direction and strategic leadership in the design, development, and deployment of AI applications using LLMs, agentic systems, and related technologies.
  3. Drive model customization and post-training — including fine-tuning, RL, and instruction/skill tuning — to adapt LLMs for chip-design coding, debugging, and reasoning tasks.
  4. Oversee development of retrieval and generation algorithms for enterprise data (text, code, waveforms, and images) to support advanced AI use cases across EDA and hardware engineering.
  5. Partner closely with engineering, research, and product teams to deliver LLM-powered solutions for engineering assistants and multi-turn, multi-modal dialogue systems.

Skills

Required

  • Python
  • data structures
  • large-scale system design
  • people-leadership
  • mentoring
  • coaching
  • building teams
  • cross-functional efforts

Nice to have

  • LLMs
  • agentic systems
  • fine-tuning
  • RL
  • instruction/skill tuning
  • retrieval algorithms
  • generation algorithms
  • multi-modal dialogue systems
  • evaluation frameworks
  • safety guardrails
  • production monitoring
  • chip design workflows
  • EDA

What the JD emphasized

  • shipping production-grade AI applications
  • technical leadership
  • managing software/AI teams
  • post-training LLMs
  • agentic systems

Other signals

  • leading teams building agentic AI solutions
  • integrating with enterprise production systems
  • delivering LLM-powered solutions for engineering assistants