Senior Software Engineer, Agentic AI

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA +5 · Remote

Senior Software Engineer to develop core libraries for Agentic Applications, focusing on building foundational technology, scalable capabilities, reusable blocks, and high-quality libraries to accelerate developer productivity and ensure agent quality. The role involves benchmarking, identifying bottlenecks, and optimizing performance, cost, and latency for agents. Collaboration with teams on data pipelines, RAG, vector databases, and GPU-optimized workflows is expected.

What you'd actually do

  1. Develop open-source libraries and tools which accelerate and optimize agent harnesses and frameworks ensuring top-tier performance, accuracy, quality, and stability.
  2. Benchmark the latest agents to identify bottlenecks and build creative solutions to increase performance, reduce cost, and improve latency.
  3. Work closely with teams building high-performance data pipelines, RAG systems, vector databases, and GPU-optimized training and inference workflows to deliver best-in-class agentic applications.
  4. Identify gaps and friction in current agent architectures, and translate insights into agentic tools that boosts developer velocity and agent quality—backed by evaluations, benchmarking, and feedback loops.
  5. Track and understand evolving agent development patterns across NVIDIA and the broader ecosystem, maintaining current knowledge of both research and commercial products.

Skills

Required

  • Rust
  • Python
  • Go
  • Node.js
  • asynchronous programming
  • callbacks
  • request lifecycles
  • event-driven systems
  • agent architectures
  • agent frameworks
  • agent harnesses
  • LLM applications
  • agent workflows
  • tool calls
  • model-provider APIs
  • cross-language APIs
  • systems-level debugging
  • performance intuition
  • open source community collaboration

Nice to have

  • evaluation/benchmarking systems for agent workflows
  • Rust systems work
  • async Rust
  • Tokio
  • serde
  • API design
  • runtime state management
  • Python native extension
  • PyO3
  • maturin
  • Python/Rust bindings
  • instrumenting third-party frameworks
  • OpenTelemetry
  • tracing
  • structured events
  • exporters
  • observability pipelines
  • middleware
  • plugin systems
  • guardrails
  • policy engines
  • request/response interception
  • maintaining open-source libraries
  • SDKs
  • internal developer platforms
  • profiling
  • optimizing runtime/library overhead
  • native bindings
  • serialization
  • middleware pipelines

What the JD emphasized

  • Hands-on experience with evolving agent architectures, multiple agents frameworks and agent harnesses.
  • Proficiency in LLM applications, agent workflows, tool calls, and model-provider APIs.

Other signals

  • building foundational technology for agents
  • scalable agentic capabilities
  • reusable building blocks for agents
  • high-quality libraries for agents
  • accelerate developer productivity for agents
  • ensure agent quality
  • critical acceleration and optimization for agents