Lead Senior Software Engineer, Agentic AI Applications

Posted 5 Days Ago
Be an Early Applicant
6 Locations
In-Office or Remote
184K-357K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Lead the design and development of agentic AI applications, mentors engineers, collaborates with cross-functional teams, and optimizes performance across distributed systems.
Summary Generated by Built In

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brain of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

NVIDIA is seeking a Senior Software Engineer to serve as a Tech Lead, driving the design and delivery of agentic blueprints and reference workflows, including the AI-Q Deep Researcher blueprint. This role focuses on crafting industry-leading agentic reference examples that demonstrate how enterprises can implement agentic AI at scale. The ideal candidate is an experienced technical leader with deep expertise in generative AI, distributed systems, and ability to convert proof-of-concept applications into products. You should be comfortable translating research and prototypes into robust, scalable, and maintainable systems while mentoring others to do the same.

What you'll be doing:

  • Design, develop, and implement agentic AI blueprints (applications) that show enterprises how to utilize and deploy this technology.

  • Lead technical reviews and provide mentorship, guiding the engineering team in building production-grade workflows and extending core GenAI SDK capabilities.

  • Develop proof-of-concept workflows rooted in first principles that apply modern data science techniques to GenAI use cases.

  • Collaborate cross-functionally with product, research, and infrastructure teams to evolve NVIDIA's agentic ecosystem, including integrations between the NeMo Agent Toolkit and other NVIDIA products and services such as the NeMo Framework, NIMs, and NVIDIA Blueprints.

  • Drive performance optimization for agentic applications across the data center, focusing on improving accuracy, reducing latency, and growing efficiency.

  • Establish engineering standards and best practices for developing, testing, and deploying agentic AI applications across distributed environments.

What we need to see:

  • BS in Computer Engineering, Computer Science, Data Science, or a related field, or equivalent experience; MS or PhD preferred

  • 8+ years of software engineering experience, including 2+ years as tech lead.

  • Proficient in Python, with at least 6+ years of experience building Python libraries or applications for enterprise customers.

  • Experience with GenAI application development using LLM frameworks (e.g., Langchain, Llamaindex, or AutoGen), evaluation systems (e.g., RAGAs), and observability platforms (e.g., Arize Phoenix, W&B Weave, or LangSmith).

  • Experience using and understanding of agentic frameworks.

  • Proficient in distributed orchestration and communication frameworks (e.g., Kafka, Ray).

  • Ability to quickly learn and apply new technologies and libraries.

  • Self-starter with a proactive work ethic, capable of working independently and successfully within a distributed team.

  • Excellent communication and collaboration skills across distributed, cross-functional teams.

Ways to stand out from the crowd:

  • Demonstrated leadership in building and scaling agentic AI applications in production.

  • Experience developing your own agents in Python or a similar language (e.g., Go).

  • Concrete examples/code of how you have profiled code in the past to identify performance bottlenecks and examples of how you mitigated these.

  • Experience developing for GPU platforms and familiarity with NVIDIA technologies (e.g., CUDA, TensorRT, Triton, NeMo) and LLM serving frameworks (e.g., Dynamo, vLLM, SGLang).

  • Experience with RAG systems and communication protocols (e.g., MCP, A2A).

With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most forward-thinking and versatile people in the world working with us, and our engineering teams are growing fast in some of the most impactful fields of our generation: Deep Learning, Artificial Intelligence, and Autonomous Vehicles. If you're a creative engineer who enjoys autonomy and shares our passion for technology, we want to hear from you.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 4, 2025.NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Top Skills

Arize Phoenix
Autogen
Cuda
Dynamo
Genai
Kafka
Langchain
Langsmith
Llamaindex
Llm Frameworks
Nemo
Python
Ragas
Ray
Sglang
Tensorrt
Triton
Vllm
W&B Weave
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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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