Job Description – Senior Application Security Developer (Python & AI Security)
Position Overview
We are seeking a Senior Application Security Developer with strong Python development expertise and hands-on experience in Application Security and AI/LLM Security.
This is a development-focused role for someone who can build, automate, and integrate security capabilities into enterprise applications and CI/CD pipelines, with a particular focus on leveraging AI to improve vulnerability detection, prioritization, analysis, and remediation.
Must-Have Requirements
- Strong hands-on Python development experience, including API development, scripting, automation, and integration.
- Strong experience with Application Security (AppSec) and secure software development practices.
- Experience integrating and automating security tooling within CI/CD and DevSecOps pipelines.
- Experience applying AI/LLM technologies to Application Security, including:
- AI-assisted SAST and SCA
- Secrets scanning
- Vulnerability prioritization
- Exploitability and reachability analysis
- Attack path analysis
- Automated remediation
- Hands-on knowledge of LLMs, AI agents and RAG architectures.
- Understanding of prompt security, AI model security, AI guardrails, runtime protection, and model lifecycle security.
- Experience developing or integrating AI-powered security tooling and capabilities.
- Strong understanding of Cloud Security and modern cloud-native application architectures.
Key Responsibilities
- Develop Python-based security applications, APIs, automation, and integrations.
- Build and enhance AppSec capabilities across the software development lifecycle.
- Integrate SAST, SCA, secrets scanning, and vulnerability management tooling into development workflows.
- Develop AI-assisted capabilities for vulnerability analysis, prioritization, exploitability assessment, and remediation.
- Build security controls and guardrails for LLM and AI-enabled applications.
- Support the implementation of AI Security Posture Management (AI-SPM) and AI asset inventory capabilities.
- Automate security processes and integrate security capabilities into CI/CD pipelines.
- Contribute to AI security standards, ML SecOps practices, and secure AI development guidelines.
Good-to-Have
- Java development experience.
- Experience building scalable, self-service security platforms for development teams.
- Experience with cloud-native security and containerized environments.
- Experience building or integrating enterprise AI/LLM security solutions.
Experience integrating APIs for AI models (OpenAI, Anthropic, or similar) Ability to translate security requirements into automated AI workflows