NVIDIA Networking is looking for a highly capable and independent Software Engineer to join the Networking SW Tools & Automation team.The team develops and customizes tools, automation, workflows, dashboards, and AI-enabled solutions that improve how the Networking SW organization plans, develops, validates, and delivers complex software products. In this role, you will work closely with SW Product Managers, Architects, R&D, QA, and Technical Program Managers (TPMs) to understand their needs, challenges, and ways of working. You will translate these needs into well-defined processes, workflows, data models, and tool requirements — and then design and develop the solutions that implement them.
AI is a core element of this role. We are looking for someone who is deeply knowledgeable and hands-on with modern AI technologies, frameworks, coding agents, and development tools; actively follows and experiments with the constantly evolving AI ecosystem; and is passionate about applying these technologies to solve real engineering and operational problems. You will use AI both to accelerate how software is developed and as a core capability within the tools and automation you build. The team operates with significant ownership and independence. We are looking for someone who can take an ambiguous problem, work across functions to understand it, structure the problem and solution, select the right technologies, and personally drive implementation from concept through production and adoption.
What you'll be doing:
- Partner with SW Product Managers, Architects, R&D, QA, and TPMs to understand workflows, difficulties, information needs, and opportunities for improvement and automation.
- Analyze existing ways of working and translate organizational needs into well-defined processes, flows, functional requirements, data models, and technical designs.
- Design, develop, and deploy tools and automation supporting the end-to-end SW lifecycle — from feature/POR definition and development through validation, release, and ongoing maintenance.
- Apply AI technologies hands-on to solve engineering and operational challenges, selecting the appropriate models, frameworks, agents, architectures, and tools for each problem.
- Develop AI-enabled applications and workflows that help users find and synthesize information, interact with engineering data, identify risks and inconsistencies, automate repetitive activities, and support better and faster decision-making. Use AI coding agents and modern AI development environments extensively to accelerate prototyping, implementation, testing, debugging, and iteration. Continuously explore emerging AI technologies and rapidly assess their applicability to real organizational needs — turning promising capabilities into practical solutions rather than technology demonstrations.
- Develop and customize solutions around platforms such as Jira and other engineering systems, including workflows, automation, integrations, and reporting.
- Build web-based tools and interactive applications that consolidate information from multiple engineering tools, databases, and APIs into coherent and actionable views.
- Develop dashboards and analytics for monitoring features, bugs, releases, milestones, dependencies, risks, execution status, and other key engineering and program indicators. Automate recurring workflows and reporting, reducing manual work while improving data quality, consistency, traceability, and visibility.
- Own solutions end-to-end — from problem discovery and requirements definition through architecture, implementation, testing, deployment, documentation, adoption, and continuous improvement.
What we need to see:
- B.Sc. in Computer Science, Software Engineering, Information Systems, or equivalent practical experience.
- 5+ years of software development, internal tools, or automation experience, preferably within a complex SW development environment.
- Strong hands-on software development capability, with demonstrated ability to independently build and deliver working applications, tools, integrations, and automation.
- Strong understanding of the end-to-end software development lifecycle — from product requirements and architecture through feature development, integration, QA, bug management, release, and program execution. The ability to engage effectively with collaborators across these subject areas, understand their needs and challenges, and translate them into effective processes, workflows, and technical solutions is crucial.
- Hands-on AI Expertise: Proven track record evaluating and applying modern models, frameworks, APIs, and AI coding agents in day-to-day development. End-to-End Delivery: Experienced in taking AI solutions from initial concept and prototyping to evaluation and production. Continuous Innovation: Passionate about experimenting with emerging AI technologies and applying them to real-world problems.
- Experience with relevant technologies such as Python, JavaScript/TypeScript, SQL, REST APIs, databases, and web technologies.
- Experience integrating multiple systems and data sources through APIs, databases, and automation frameworks.
- Strong systems and process thinking — able to understand complex multi-functional workflows, identify gaps and inefficiencies, and translate them into scalable technical solutions. Ability to move effectively between the user and process perspective, system and data architecture, and hands-on implementation details.
- Demonstrated ability to operate independently in an ambiguous environment, structure complex problems, identify the right collaborators and requirements, and drive solutions to completion. Strong product and user approach — focused on building solutions that are simple, effective, maintainable, scalable, and adopted in practice. Excellent communication and interpersonal skills, with the ability to work effectively across technical subject areas and organizational levels.
Ways to stand out from the crowd:
- Experienced in developing AI-native internal tools, automation platforms, and agentic workflows integrated with enterprise systems and APIs. Hands-on expertise with agent frameworks, knowledge-based architectures, and modern AI coding environments like Claude Code and Codex to boost engineering productivity.
- Background with developing web applications and interactive data-driven user interfaces.
- Experience developing and customizing Jira workflows, APIs, plugins, automation, dashboards, and integrations.
- Experience developing dashboards, analytics, and automated reporting across multiple engineering data sources.
- Good understanding of the end-to-end software development lifecycle, including product requirements, architecture, feature development, QA, bug management, release management, and program execution. Proven track record to turn manual, fragmented, or inefficient workflows into integrated, intelligent, and automated solutions.