Senior Software Engineer – Platform Engineering

NVIDIA is seeking a Senior Software Engineer – Platform Engineering to build next-generation AI platforms and products. You will play a pivotal role in shaping the architecture, development, and scaling of software systems.

Job Overview: As a Senior Software Engineer, you will collaborate with cross-functional teams to deliver end-to-end intelligent experiences across applications. You will ensure reliability, safety, and performance of autonomous systems operating at scale.

Responsibilities:

• Collaborate with cross-functional teams to deliver end-to-end intelligent experiences across applications.
• Ensure reliability, safety, and performance of autonomous systems operating at scale.
• Integrate agents with enterprise data sources, APIs, and internal microservices to enable real-world actions.
• Architect and build agentic AI systems that leverage LLMs for reasoning, planning, and tool orchestration across enterprise workflows.
• Develop scalable platforms for retrieval-augmented generation (RAG), long-term memory, and contextual reasoning.
• Establish best practices for agent evaluation, guardrails, and human-in-the-loop workflows.
• Mentor engineers and provide technical leadership in designing complex distributed AI systems.
• Stay at the forefront of advancements in LLMs, agent frameworks, tool use, reasoning architectures, and open-source ecosystems.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (or equivalent experience).
• 12+ years of experience building large-scale distributed systems and cloud-native applications (Python preferred).
• Strong programming skills across multiple languages and modern software stacks.
• Hands-on experience with test automation, production testing, and automation frameworks.
• Solid understanding of Linux, embedded systems, firmware, and hardware/software integration.
• Deep knowledge of IT Service Management (ITSM) and ServiceNow (HR, Security, Finance modules preferred).
• Strong experience designing and deploying LLM-powered systems, including RAG, tool use, and agent-based architectures.
• Deep understanding of agentic AI paradigms (planning, memory, tool invocation, multi-step reasoning).
• Proven ability to design systems with high reliability, scalability, and performance.
• Hands-on experience deploying applications in Kubernetes environments.
• Proven track record leading complex technical initiatives and mentoring high-performing teams.

Benefits: You will also be eligible for equity and benefits.