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Remote Senior AI Application Security Engineer
Kforce • San Ramon, CA
No Relocation
Posted: June 16, 2026
Additional Content
Responsibilities
- Design and secure AI-driven development workflows using tools like Claude Code, Cline, Aider, Copilot, and similar platforms
- Build and orchestrate AI-assisted pipelines for code generation, testing, review, and remediation across the SDLC
- Create reusable patterns, prompts, and agent workflows that improve developer productivity while maintaining security standards
- Integrate AI tooling into CI/CD pipelines to automate vulnerability detection, prioritization, and remediation
- Lead threat modeling and security design for modern applications, APIs, and AI-enabled features
- Develop lightweight automation and scripts to scale security coverage and streamline engineering workflows
- Partner with engineering teams to embed secure-by-design practices into AI-assisted development
- Evaluate and operationalize new AI tools, frameworks, and orchestration patterns
- Mentor developers on effective and responsible use of AI-powered coding tools
Requirements
- Bachelor's degree in Computer Science, Cybersecurity, Information Assurance, Software Engineering, or a related field, or an equivalent combination of education and experience
- Preferred certifications: CSSLP, OSCP, GWEB, or GWAPT
- 7+ years of experience in application security, software engineering, or DevSecOps in cloud-native environments
- Strong experience building or securing modern development workflows and pipelines
- Hands-on, daily use of AI-powered coding tools (e.g., Copilot, Claude Code, Cline, Aider, or similar)
- Experience designing AI workflows, agent-based systems, or prompt-driven development processes
- Proficiency in at least one core programming language (Python, JavaScript/TypeScript, Java, or similar)
- Solid understanding of secure coding practices, API security, and modern authentication patterns
- Familiarity with common application security testing approaches and automation methods
- Experience working in cloud environments and integrating tools into CI/CD pipelines
- Exposure to LLM security risks preferred
- Experience with AI orchestration frameworks, RAG pipelines, or agent-based architectures preferred
- Background building internal developer tools or enablement programs preferred