Nvidia Principal Software Engineer - Employee Productivity 

United States, California 

534071028

What you will be doing:

• Own the end-to-end lifecycle of software development, from concept to deployment, including architecture design, development, testing, and scaling.

• Develop high-quality, scalable, and efficient software solutions that integrate generative AI capabilities.

• Ensure system reliability, performance, and security at scale.

• Drive the development process from conception to deployment, ensuring fast iterations without compromising quality and security.

• Plan and implement strategies for scalability and future growth, anticipating technological advancements and business needs.

• Keep abreast of emerging trends and technologies in AI, software development, and system architecture.

• Are a strong advocate of software engineering best practices and bring a disciplined approach to testing, continuous delivery, and reducing technical debt

What we need to see:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field or equivalent experience.

• 12+ years of proven experience in software engineering experience on large-scale production systems

• Proven expertise of performance, reliability in sophisticated distributed systems and the teams that build them.

• Strong proficiency in multiple programming languages and technologies relevant to AI and system development.

• Proven track record to lead sophisticated projects and deliver results in a fast-paced, multifaceted environment.

• Experience in all phases of the software development lifecycle, including design, architecture, development, testing, security, and deployment.

• Deep understanding of building successful platforms and tools for developers in a large scale environment

• Experience with Agile methodologies and a mindset of continuous learning and adaptation.

• Excellent leadership, problem-solving, analytical and communication skills, capable of inspiring and leading a technical team.

Ways to stand out from the crowd:

• Prior experience in employee productivity software or generative AI.

• Fascinated by unique and difficult problems - resilient and persistent in the pursuit of solutions.

• Self-motivation and a drive to get things to “done”.

• Experience with Machine Learning and Data Analytics.