Lead Senior Software Engineer, Agentic AI Applications at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, AIIndustries

Requirements

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

Responsibilities

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

Skills

Generative AI

Agentic AI

Distributed Systems

GenAI SDK

NeMo Agent Toolkit

AI Blueprints

Data Science

Scalable Systems

Tech Lead

Mentoring

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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