Senior Software Engineer — Agentic AI and Foundations

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-accelerated 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, we are increasingly known as the AI computing company.

Now we need a senior staff-level, hands-on engineer to make them bulletproof and to architect the next generation of agent infrastructure. This is not a research role.

• 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 strong patterns for testing, debugging, CI/CD, safe rollout, auto-update mechanisms, monitoring, incident response, and operational excellence so our Agentic AI applications behave like mature software, not prototypes.
• Build reusable capabilities that support 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 technologies such as Nemotron, NVIDIA AI Blueprints, and related platform capabilities in enterprise production settings.
• Codify architecture, shared components, documentation, and operational playbooks; mentor engineers; and create foundations that are durable, reusable, and broadly owned.
• Define the core architecture for how AI agents discover one another, collaborate securely, build trust, and operate under enterprise governance.
• Partner closely with domain AI engineers, product managers, designers, infrastructure teams, IT, and research to deliver measurable outcomes across employee productivity, engineering efficiency, AIOps, and enterprise operations.

• BS, MS, or equivalent experience in Computer Science or a related field.
• 12+ years 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.
• Solid experience building modern applications across frontend, backend, and platform layers. This may include technologies such as Type Script/JavaScript, React, Electron or similar desktop frameworks, Python, Go, Java, APIs, data systems, and distributed infrastructure.
• Proven track record taking 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 such as 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.

• 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…