AppSec Engineer - Secure SDLC & AI Security(Remote/Hybrid)

LAM RESEARCH Corporation

Fremont (CA)

Hybrid

USD 92,000 - 211,000

Full time

14 days+

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Job summary

Lam Research is seeking an Application Security professional to join the Information Security team in the San Francisco Bay Area. You will support Secure SDLC, risk assessments, threat modeling, and AI-related security reviews across Lam-developed applications and AI-enabled solutions.

The role emphasizes secure software delivery, collaboration with engineering teams, and implementing tools like SAST, DAST, and SCA in CI/CD.

Qualifications

Bachelor’s degree in Computer Science, Information Security, Information Technology, Engineering, or related field.
3+ years of experience in information security, application security, product security, software engineering, DevSecOps, or related technical field.
Hands-on experience with application security tools such as SAST, DAST, SCA, secrets scanning, container scanning, or vulnerability management platforms.

Responsibilities

Support the objectives of the Application Security team by contributing to secure design, Secure SDLC execution, and product security reviews.
Assist with application risk assessments, secure design reviews, threat modeling, code review, vulnerability assessment, and penetration testing.
Support the integration and operational use of application security tools, including SAST, SCA and DAST, and other DevSecOps capabilities in CI/CD pipelines.
Work with development teams to identify and document security requirements, common application risks, and required controls based on application risk level, data sensitivity, exposure, and system interconnections.
Help engineering teams interpret and apply secure coding standards, OWASP guidance, internal Secure SDLC requirements, and product security best practices.
Assist in reviewing AI-related security risks, including prompt injection, insecure model/tool integration, data leakage, excessive autonomy, insecure AI outputs, model sourcing, sensitive data exposure, and lack of human-in-the-loop controls.
Participate in AI-related security initiatives, including secure AI model usage, AI-assisted development governance, AI-enabled application review, and secure MLOps process improvement.
Research, evaluate, and help pilot new security capabilities, automation, and AI-assisted AppSec workflows under guidance from senior security engineers.
Document findings, recommendations, and review outcomes clearly for application teams, security leadership, and governance tracking.
Partner with cross-functional teams to improve secure development practices and reduce application and product security risk.