Principal Software Engineer — Agentic AI Applications and Foundations

Details

NVIDIA's Enterprise AI team builds intelligent AI agents that transform how NVIDIA operates, including smart personal assistants, engineering productivity tools, data-driven analytics, and supply-chain optimization. These agents are live in production and used across the company. NVIDIA is seeking a principal-level, hands-on engineering leader to improve the reliability of existing AI applications and architect the next generation of agent infrastructure. This is an engineering role focused on production systems rather than AI research, with an emphasis on reliability, polish, user trust, full-stack development, and scalable architecture.

Responsibilities

• Improve reliability, performance, observability, release confidence, and end-user experience across desktop, web, and service-based AI products.
• Design and build resilient frontends, backend APIs, distributed services, data flows, and deployment systems that scale to enterprise use.
• Establish patterns for testing, debugging, CI/CD, safe rollout, auto-update mechanisms, monitoring, incident response, and operational excellence.
• Build reusable capabilities for multiple agent domains, including orchestration services, deep-agent workflows, memory and context services, evaluation frameworks, telemetry, and policy-aware tool integration.
• Help validate and operationalize Nemotron, NVIDIA AI Blueprints, and related platform capabilities in enterprise production settings.
• Codify architecture, shared components, documentation, and operational playbooks.
• Mentor engineers and create durable, reusable foundations with broad ownership.
• Define the core architecture for how AI agents discover one another, collaborate securely, build trust, and operate under enterprise governance.
• Partner with domain AI engineers, product managers, designers, infrastructure teams, IT, and research to deliver outcomes across employee productivity, engineering efficiency, AIOps, and enterprise operations.

Requirements

• Bachelor's degree, master's degree, or equivalent experience in Computer Science or a related field.
• 15+ years of experience building and operating production software systems, including significant experience leading architecture and delivery across the full stack.
• Familiarity with enterprise application deployment, security, authentication, device management, and application lifecycle management.
• Experience building modern applications across frontend, backend, and platform layers. Relevant technologies may include TypeScript/JavaScript, React, Electron or similar desktop frameworks, Python, Go, Java, APIs, data systems, and distributed infrastructure.
• Proven ability to take complex products from prototype to reliable, secure, well-operated production systems.
• Deep expertise in testing strategy, release engineering, observability, performance tuning, and incident response.
• Experience building shared services, internal platforms, SDKs, or core infrastructure used by multiple teams or products.
• Working knowledge of modern AI application patterns, including LLM-powered applications, RAG, tool use, CLI-based workflows, reusable skills, MCP-based integrations, evaluation loops, memory systems, and agentic workflows.
• Strong judgment, communication, and cross-functional leadership skills, with the ability to influence across teams while remaining highly hands-on.

Preferred Qualifications

• Experience hardening desktop or client applications at scale, including installers, auto-update systems, crash recovery, and enterprise distribution.
• A track record of improving engineering velocity and consistency through common frameworks, platform services, design patterns, and developer tooling.
• Experience building reusable infrastructure for AI products, such as orchestration layers, memory and context services, evaluation platforms, human-in-the-loop workflows, or policy and safety controls.
• Familiarity with identity, discovery, trust, reputation, or graph-based systems relevant to large-scale agent collaboration.
• Experience with GPU-accelerated systems or NVIDIA AI technologies such as NeMo, NIM, Nemotron, TensorRT-LLM, or AI Blueprints.

Compensation and Benefits

• Base salary range: USD 272,000–431,250 per year.
• Eligible for equity and benefits.
• Applications will be accepted at least until June 12, 2026.
• NVIDIA uses AI tools in its recruiting processes.
• NVIDIA is committed to an inclusive work environment and is an equal opportunity employer.