Tanium Software Engineer II, AI Security at Tanium designs and develops high-scale, distributed backend systems to secure AI agents and endpoints. Focus on backend engineering with LLM APIs, tool-calling frameworks, and Model Context Protocol.
Responsibilities
Design and develop high-scale, distributed backend systems that give customers visibility into and control over agentic AI across their environments
Build services and integrations using LLM APIs, tool-calling frameworks, and the Model Context Protocol (MCP), and design retrieval (RAG) and data pipelines that support AI-driven capabilities
Use AI coding assistants and agent tooling effectively in day-to-day development, and review, refactor, and debug AI-generated code with sound judgment
Design and develop robust, scalable, and maintainable software features and systems across the full software development lifecycle
Architect technical solutions that meet complex product requirements while balancing performance, reliability, and security considerations
Collaborate with product management, UX, and peer engineers to define requirements, estimate effort, and deliver high-quality solutions on schedule
Lead code reviews and provide constructive technical feedback to elevate engineering standards and promote best practices across the team
Identify, troubleshoot, and resolve complex software defects and performance bottlenecks in both development and production environments
Mentor and support the growth of junior and mid-level engineers through knowledge sharing, pairing, and technical guidance
Contribute to the continuous improvement of engineering processes, tooling, and development practices to increase team velocity and code quality
Partner with security and infrastructure teams to ensure software is developed and deployed in alignment with Tanium's security and compliance standards
Education
Qualification
PreferredOtherExperience with version control systems
Required
Experience building backend services and enterprise web applications that serve large user bases (for example, millions of users)
Experience with the full software development lifecycle, including requirements analysis, design, implementation, testing, and deployment
Preferred: Experience working in a cybersecurity, SaaS, or enterprise software environment
Preferred: Foundation in security principles, such as secure design, authentication and authorization, and threat modeling
Preferred: Familiarity with cloud infrastructure platforms such as AWS, Azure, or Google Cloud
Other
Proficiency in one or more modern programming languages such as Go, C++, Java, Python, or similar
Ability to prompt AI coding tools effectively and to read, understand, refactor, and debug the resulting code, regardless of language
Strong understanding of software design patterns, data structures, and algorithms
Experience with version control systems, particularly Git, and collaborative development workflows
Preferred: Familiarity with containerization and orchestration technologies such as Docker and Kubernetes
Preferred: Experience with CI/CD pipelines and automated testing frameworks
