Senior Application Security Developer , AI Security

Autodesk Autodesk · Enterprise · AMER - Canada - Ontario - Offsite +1

Senior Application Security Developer with a focus on AI Security at Autodesk. The role involves securing AI-enabled applications, particularly LLM-powered features, agent-based systems, and AI-assisted development workflows. Responsibilities include leading security assessments, defining secure patterns, embedding security controls, developing secure coding guidelines, evaluating runtime controls, integrating AI security testing into CI/CD, and providing developer education. Requires 5+ years of application security experience and familiarity with AI/LLM systems.

What you'd actually do

  1. Lead security assessments of AI-enabled applications, including LLM-integrated systems, agents, and copilots, with a focus on real-world abuse scenarios and adversarial behavior
  2. Define and implement secure-by-default patterns for AI-assisted development, including guidance for tools such as Cursor, Claude, and other IDE-integrated copilots
  3. Partner with engineering teams to shift security left, embedding AI security controls into design, development, and code review processes
  4. Develop and maintain secure coding guidelines for AI systems, including safe prompt construction, output handling, data protection, and model interaction boundaries
  5. Evaluate and improve runtime security controls for AI systems, including guardrails, input/output validation, policy enforcement, and monitoring for anomalous behavior

Skills

Required

  • 5+ years of experience in application security, product security, or related fields
  • Strong understanding of OWASP Top 10 and application/API security fundamentals (auth, authz, data protection)
  • Experience with secure development practices (threat modeling, design reviews, code reviews, shift-left security)
  • Hands-on experience securing modern applications, with exposure to or strong interest in AI/LLM systems
  • Experience identifying and mitigating vulnerabilities such as injection, data leakage, insecure deserialization, and access control issues
  • Familiarity with DevSecOps practices and integrating security into CI/CD pipelines
  • Proficiency in scripting or programming (Python, JavaScript, or Go)
  • Strong analytical and problem-solving skills
  • Ability to communicate complex security risks clearly to engineering teams

Nice to have

  • Familiarity with OWASP LLM Top 10 and AI-specific risks (prompt injection, model misuse, unsafe tool invocation)
  • Experience working with LLM-powered applications, copilots, or agent-based systems
  • Knowledge of AI security controls such as guardrails, prompt validation, and model monitoring
  • Experience with security testing approaches such as red teaming or adversarial testing
  • Familiarity with cloud-native environments (AWS, Azure, GCP)
  • Experience building security guidelines, frameworks, or developer training materials

What the JD emphasized

  • AI Security Focus
  • LLM-powered features
  • agent-based systems
  • AI-assisted development workflows
  • prompt injection
  • data leakage
  • unsafe tool usage
  • AI security practices
  • AI-enabled applications
  • LLM-integrated systems
  • agents
  • copilots
  • AI security controls
  • AI security risks
  • AI security posture
  • AI/LLM systems
  • AI-specific risks
  • AI security controls
  • AI security
  • AI security

Other signals

  • securing AI-enabled applications
  • LLM-powered features
  • agent-based systems
  • AI-assisted development workflows
  • prompt injection
  • data leakage
  • unsafe tool usage