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Salary: USD 166,500 - 291,400 / annual
ServiceNow is seeking a Staff Software Engineer to join the Software Asset Management (SAM) product team. This role focuses on building high-quality, scalable solutions that help organizations manage software licensing and compliance with precision. You will own the full software development lifecycle—from design and implementation through testing and delivery—while collaborating closely with product managers, architects, and quality engineers.
Key responsibilities include:
- Design and implement high-quality, clean, scalable, and reusable code following best practices in software architecture and processes (code reviews, unit testing, CI/CD integration)
- Own your code end-to-end: from design through implementation, test automation, and production delivery
- Partner with product managers to define feature sets that solve real customer problems
- Work with architects to shape product design and with QE teams to enhance quality and performance
- Contribute to new product features and enhance existing offerings
- Mentor peers and promote knowledge-sharing across the engineering team
- Troubleshoot complex systems and optimize performance across the stack
The SAM team is deeply aligned with company priorities and market expectations, delivering solutions that matter to 85% of the Fortune 500. You'll work in a culture that values craftsmanship, quality, and innovation, with opportunities to work symbiotically with AI and automation tools that enhance engineering excellence.
REQUIREMENTS:
- 8+ years of software engineering experience with a track record of delivering high-quality products
- Proficiency in Python, Java, or similar object-oriented languages
- Experience with modern front-end frameworks (Angular, React, or Vue)
- Strong knowledge of data structures, algorithms, object-oriented design, design patterns, and performance optimization
- Familiarity with automated testing frameworks (JUnit, Selenium, TestNG) and CI/CD pipeline integration
- Understanding of software quality principles including reliability, observability, and production readiness
- Ability to troubleshoot complex systems and optimize performance across the stack
- Experience with AI-powered tools or workflows, including validation of datasets, model predictions, and inference consistency
- Comfort with development tools (IDEs, debuggers, profilers, source control, Unix-based systems)
- Critical thinking about integrating AI into work processes, decision-making, or problem-solving
