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.
What we need to see
BS, MS, or equivalent experience in Computer Science or a related field.
15+ 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 TypeScript/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. You do not need to be a research scientist, but you should know how to build reliable, production-grade systems around AI.
Strong judgment, communication, and cross-functional leadership skills, with the ability to influence across teams while remaining highly hands-on.
Ways to stand out from the crowd
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/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.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until June 12, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
