Software Engineer

It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started.

Join us to put AI to work for people.

Job Summary

The Software Engineer designs, builds, and ships features for the Strategic Portfolio Management (SPM) suite of products, which helps organizations align work with business objectives, manage demand, resources, and projects, and accelerate product and service delivery. This role combines strong engineering execution with product judgment. The engineer works closely with product managers to understand customer problems, shape solutions, and deliver them end to end. The role also builds AI-native features and uses AI tools to accelerate design, development, testing, and delivery.

For positions in this location, we offer a base pay of $125,700 - $160,300 , plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location.

Responsibilities

Design, develop, and deliver features for the Portfolio Management suite.; Build AI-native features that use generative and agentic capabilities to improve planning workflows, insights, and user experience.; Apply AI tools effectively across the development lifecycle, including code generation, test creation, debugging, documentation, and code review, while validating output for correctness, security, and maintainability.; Partner with product managers to translate customer needs into well-scoped technical solutions and to weigh trade-offs between user value, complexity, and delivery timelines.; Write clean, tested, and maintainable code with automation and participate in code reviews, design reviews, and release activities, and contribute to team engineering practices.; Investigate and resolve production issues, including P1 escalations during US business hours, and drive root cause analysis and preventive fixes.; Contribute to platform security, accessibility (WCAG), and quality improvements.

Requirements

Bachelor's degree in Computer Science, Engineering, or a related field, with 3–5 years of professional software engineering experience, or a Master's degree in a related field with 2–3 years of professional software engineering experience.; Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry.; Demonstrated experience building applications full stack applications using modern UX frameworks, JavaScript/TypeScript and a server-side language (for example, Java or Python).; Builder mindset: thinks like a product manager, designer, engineer, and tester at the same time, weighing user value, usability, technical design, and quality risk before committing to a solution.; Demonstrated effective use of AI tools (such as coding assistants, LLM-based tools, or AI-enabled testing) to improve engineering productivity, and sound judgment about when to rely on AI output and when to verify it.; Strong communication skills and the ability to work with product, QE, and platform partners.; Familiarity with developing products that are accessibility compliant (WCAG).