Senior AI Infrastructure Software Engineer

NVIDIA-posted 8 days ago
Full-time • Mid Level
Austin, CA
5,001-10,000 employees
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You will collaborate closely with researchers to design and scale agents - enabling them to reason, plan, call tools and code just like human engineers. You will work on building and maintaining the core infrastructure for deploying and running these agents in production, powering all our agentic tools and applications and ensuring their seamless and efficient performance. If you're passionate about the latest research and cutting-edge technologies shaping generative AI, this role and team offer an exciting opportunity to be at the forefront of innovation.

  • Design, develop, and improve scalable infrastructure to support the next generation of AI applications, including copilots and agentic tools.
  • Drive improvements in architecture, performance, and reliability, enabling teams to bring to bear LLMs and advanced agent frameworks at scale.
  • Collaborate across hardware, software, and research teams, mentoring and supporting peers while encouraging best engineering practices and a culture of technical excellence.
  • Stay informed of the latest advancements in AI infrastructure and contribute to continuous innovation across the organization.
  • Master or PhD or equivalent experience in Computer Science or related field, with a minimum of 5 years in large-scale distributed systems or AI infrastructure.
  • Advanced expertise in Python (required), strong experience with JavaScript, and deep knowledge of software engineering principles, OOP/functional programming, and writing high-performance, maintainable code.
  • Demonstrated expertise in crafting scalable microservices, web apps, SQL, and NoSQL databases (especially MongoDB and Redis) in production with containers, Kubernetes, and CI/CD.
  • Solid experience with distributed messaging systems (e.g., Kafka), and integrating event-driven or decoupled architectures into robust enterprise solutions.
  • Practical experience integrating and fine-tuning LLMs or agent frameworks (e.g., LangChain, LangGraph, AutoGen, OpenAI Functions, RAG, vector databases, timely engineering).
  • 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.
  • You will also be eligible for equity and benefits .
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