Senior Software Engineer, Agentic AI

at Nvidia
📍 Santa Clara, United States
USD 148,000-287,500 per year
SENIOR
✅ On-site

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Kafka @ 6 Python @ 6 Spark @ 6 Distributed Systems @ 6 Data Science @ 4 Communication @ 4 gRPC @ 6 LLM @ 4 CUDA @ 3 GPU @ 3

Details

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. Today, NVIDIA is focusing on the unlimited potential of AI to define the next era of computing, with GPUs acting as the brains of computers, robots, and self-driving cars.

Responsibilities

  • Implement new features of GenAI SDKs enabling LLM agents to expand to new use cases and larger deployment configurations.
  • Develop proof-of-concept workflows applying modern data science techniques to GenAI use cases.
  • Collaborate with engineers to optimize agentic applications across data centers to improve accuracy, reduce latency, and enhance efficiency.
  • Build integrations between the AIQ toolkit and NVIDIA products like NeMo Framework, NIMs, and NVIDIA Blueprints.
  • Work with data scientists and ML/DL engineers to transition from POCs to production-ready pipelines and deployments.

Requirements

  • BS in Computer Engineering, Computer Science, Data Science, or closely related field (or equivalent experience).
  • At least 5 years of experience proficient in Python, building libraries or applications for enterprise customers.
  • Experience with GenAI application development using LLM frameworks (e.g., Langchain, Llamaindex, AutoGen), evaluation systems (e.g., RAGAs), and observability platforms (e.g., Arize Phoenix, W&B Weave, LangSmith).
  • Understanding of agent architectures, RAG systems, and communication protocols (e.g., MCP, Google A2A).
  • Strong problem-solving skills focused on efficiency.
  • Ability to learn and apply new technologies quickly.
  • Self-starter capable of working independently and in distributed teams.
  • Excellent communication skills for cross-functional collaboration.

Ways to Stand Out

  • MS, PhD or equivalent experience in relevant fields.
  • Experience developing for GPU platforms and familiarity with NVIDIA technologies such as CUDA, TensorRT, Triton, NeMo; LLM serving frameworks like Dynamo, vLLM, SGLang.
  • Proficiency in distributed systems and communication frameworks such as Ray, Dask, Spark, gRPC, Kafka, nats.io.
  • Proven ability to prototype and productionize features for large-scale high concurrency agentic apps.
  • Contributions to open-source Python projects.

Benefits

  • Base salary range: $148,000 - $287,500 USD, determined by location, experience, and internal pay parity.
  • Eligibility for equity and various benefits offered by NVIDIA.

NVIDIA is an equal opportunity employer committed to diversity and inclusion.