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Job Description
Company Description 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 Description Please Note:
This position will include supporting our US Federal customers. This position requires passing a ServiceNow background screening, USFedPASS (US Federal Personnel Authorization Screening Standards). This includes a credit check, criminal/misdemeanor check and taking a drug test. Any employment is contingent upon passing the screening. Due to Federal requirements, only US citizens, US naturalized citizens or US Permanent Residents, holding a green card, will be considered. About the Team The engineering organization is a dynamic group of builders, problem-solvers, and infrastructure innovators dedicated to delivering scalable, secure, and AI-powered platforms that elevate how organizations work. We value resilient architecture, automation-first thinking, and a culture of continuous improvement. Every engineer here plays a key role in shaping the reliability, security, and operational excellence of our products. What you get to do in this role: Design, develop, and maintain infrastructure, including architecting and implementing robust infrastructure to support CPQ (Configure, Price, Quote) products, ensuring dependability and scalability throughout the lifecycle. Develop and test software applications, including writing, testing, and refining software in Python, adhering to company requirements and best practices for maintainable and efficient code. Build, deploy, and manage applications using container technologies such as Docker and orchestration tools like Kubernetes, optimizing for automation and scalability. Manage and evolve infrastructure across Google Cloud Platform (GCP), Azure, and AWS, utilizing native services for high availability, resilience, security, and multicloud interoperability. Apply core concepts such as software development lifecycles, automation, and scalable architecture in every stage of product delivery. Develop secure architecture, conduct code reviews for security vulnerabilities, and institute thorough software verification and testing procedures. Oversee deployment, monitoring, and maintenance of the CPQ suite of microservices, including several AI-driven components, ensuring reliable operations across environments. Collaborate with AI/ML teams to deploy and support intelligent microservices, gaining hands-on experience with data science implementations and real-world applications. Perform routine and advanced tasks on PostgreSQL databases, such as designing schemas, optimizing queries, and ensuring data consistency and processing efficiency. Provide expert application support for SaaS CPQ solutions by troubleshooting technical issues and ensuring smooth operation. Contribute to the design and implementation of new products and features while also enhancing the existing product suite Be a mentor for colleagues and help promote knowledge-sharing Qualifications To be successful in this role you have: 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. Experience in using AI Productivity tools such as Windsurf, Cursor, etc. Is a plus or nice to have. Experience leveraging AI/ML in engineering and quality processes (e.g., automated testing, AI-driven insights, intelligent monitoring). 6+years of experience in DevOps engineering, with a track record of delivering high-quality products. Experience with Azure Government Community Cloud (GCC) and hyperscaler environments operating under FedRAMP or regulated government cloud standards. Experience with GCP, Azure, or AWS. Proficiency in Python. Experience with software development lifecycle (SDLC) and automation — implementing automation, testing strategies, and CI/CD practices across delivery stages using GitHub for version control and GitHub Actions for automated build, test, and deployment workflows. Experience with PostgreSQL database management. Experience with AI/ML microservice integration. Experience with Docker and Kubernetes. Experience with regulated markets on Azure is a plus.
