3 days ago
Base Salary
$168k - $322k/yr
Responsibilities
- Architect and build agentic AI systems using LLMs for reasoning, planning, memory, and tool orchestration.
- Develop scalable platforms for retrieval-augmented generation, contextual reasoning, evaluation, and observability.
- Integrate agents with enterprise data sources, APIs, and internal services to enable business workflow actions.
- Build and deploy reliable, scalable cloud-native applications in Kubernetes and hybrid environments.
- Collaborate with Cloud, AI/ML, and Generative AI teams to deliver end-to-end intelligent experiences.
- Lead complex technical initiatives and mentor high-performing teams.
- Apply test automation, production testing, and automation frameworks to software systems.
- Work with Linux, embedded systems, firmware, and hardware/software integration.
Requirements
- Bachelor’s or master’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
- 8+ years of experience building large-scale distributed systems and cloud-native applications, with Python preferred.
- Strong experience designing and deploying LLM-powered systems using RAG, tool use, and agent-based architectures.
- Deep understanding of agentic AI paradigms, including planning, memory, tool invocation, and multi-step reasoning.
- Experience with agent frameworks and orchestration tools such as LangChain or similar technologies.
- Experience designing systems for high reliability, scalability, and performance.
- Hands-on experience deploying applications in Kubernetes environments and working in cloud or hybrid environments.
- Strong programming skills across multiple languages and modern software stacks.
- Experience with IT Service Management and ServiceNow; HR, Security, or Finance modules are preferred.
- Experience enhancing enterprise efficiency and employee experience through Generative AI solutions.
- Experience with cloud platforms, Kubernetes, and Docker.
- Demonstrated ability to lead complex technical initiatives and mentor teams.
Benefits
- Eligible for equity and benefits.
- Base salary is provided in the posting by level and varies based on location, experience, and comparable employee pay.
- Applications are accepted at least until October 9, 2026.
Tech Stack
Categories
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.