ServiceNow is looking to solve the problem of transforming how work is done by delivering scalable, AI-powered software products that elevate organizational efficiency and productivity.
Requirements
- Proficiency in Python, Java, or similar object-oriented languages.
- Experience with modern front-end frameworks such as Angular, React, or Vue.
- Strong knowledge of data structures, algorithms, object-oriented design, design patterns, and performance optimization
- Familiarity with automated testing frameworks (e.g., JUnit, Selenium, TestNG) and integrating tests into CI/CD pipelines
- Understanding software quality principles including reliability, observability, and production readiness.
- Ability to troubleshoot complex systems and optimize performance across the stack.
- Comfort with development tools such as IDEs, debuggers, profilers, source control, and Unix-based systems
Responsibilities
- Design and develop scalable, maintainable, and reusable software components with a strong emphasis on performance and reliability.
- Collaborate with product managers to translate requirements into well-architected solutions, owning features from design through delivery
- Build intuitive and extensible user experiences using modern UI frameworks, ensuring flexibility for customer-specific needs.
- Contribute to the design and implementation of new products and features while enhancing existing product capabilities.
- Integrate automated testing into development workflows to ensure consistent quality across releases.
- Participate in design and code reviews ensuring best practices in performance, maintainability, and testability.
- Develop comprehensive test strategies covering functional, regression, integration and performance aspects
Other
- Experience in leveraging critical thinking about how to integrate AI into work processes, decision-making, or problem-solving.
- 4–10 years of experience in software engineering, with a track record of delivering high-quality products.
- Experience with AI-powered tools or workflows, including validation of datasets, model predictions, and inference consistency.
- Foster a culture of continuous learning and improvement by sharing best practices in engineering and quality
- Promote a culture of engineering craftsmanship, knowledge-sharing, and thoughtful quality practices across the team.
