Senior Software Engineer, AI Security

Summary

Join ServiceNow as a Senior Software Engineer and play a critical role in developing specialized tools and services to secure ServiceNow’s cutting-edge Agentic AI solutions. Collaborate with architects, researchers, and security experts to translate security research into robust, production-ready software systems. Develop, maintain, and optimize high-quality backend software systems and APIs designed for Agentic AI security and safety. Translate advanced security research findings into scalable software tools and services. Contribute to engineering best practices and ensure technical excellence. Take ownership of significant features and services from conceptualization through deployment. Build and deploy data pipelines and ML model training pipelines.

Requirements

• 4+ years of professional software development experience, emphasizing backend engineering
• Deep expertise in Java, including algorithms, data structures, object-oriented design, and performance optimization
• Strong knowledge of RESTful API design, microservices architectures, and database concepts (SQL/NoSQL)
• Experience in developing and maintaining secure, scalable backend systems and services

Responsibilities

• Develop, maintain, and optimise high-quality backend software systems and APIs, specifically designed for Agentic AI security and safety
• Translate advanced security research findings into scalable software tools, services, and guardrails for securing AI models
• Collaborate with AI security researchers and architects to implement practical solutions for identifying and mitigating vulnerabilities unique to Agentic AI systems
• Contribute to engineering best practices (code reviews, unit testing, CI/CD pipelines) and ensure technical excellence across the development lifecycle
• Take ownership of significant features and services from conceptualization through deployment, continuously improving existing solutions
• Build and deploy data pipelines and ML model training pipelines

Preferred Qualifications

• Experience developing security or AI security products, including exposure to ML model security, adversarial attacks, and vulnerability assessment frameworks
• Practical experience integrating AI/ML technologies and APIs into backend systems
• Hands-on experience with cloud environments (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes)
• Familiarity with industry-standard security frameworks and best practices relevant to AI and data security (e.g., OWASP LLM Top 10)