Integrate security practices throughout the SDLC in partnership with engineering and DevOps teams.
Promote secure coding standards, tooling, and automation.
Design, implement, and maintain security controls within CI/CD platforms (GitHub Actions, Jenkins, GitLab, Azure DevOps, etc.).
Ensure software integrity through code signing, artifact validation, and provenance.
Automate SAST, DAST, SCA, and container image scanning in the build and release pipelines.
Automated AI specific vulnerability scanning into CI/CD to catch insecure LLM orchestration patters
Identify and remediate misconfigurations and access control gaps in pipeline environments.
Design, deploy, and tune WAF rules and API security protections.
Conduct API risk assessments and promote secure API design patterns.
Perform secure code reviews and support automated security testing coverage across pipelines.
Triage, prioritize, and track vulnerabilities across source code, CI/CD pipelines, and deployed services.
Facilitate threat modeling for applications, APIs, and delivery pipelines.
Perform threat modeling on RAG architecture and autonomous agents
Expand security automation around API discovery, dependency scanning, SBOM generation, and secrets detection.
Mentor engineering teams on secure coding and secure pipeline practices.
Support the Security Champions program.
Act as a trusted advisor to product, platform engineering, and DevOps teams, translating technical risks into business impact.
Partner with SOC/IR teams during software supply chain or pipeline-related security incidents.
Assess and guide the secure adoption of AI capabilities within enterprise applications—focusing on data security, access controls, model input/output handling, and preventing misuse within internal systems.
Leverage AI‑powered security tools to identify anomalies, code risks, and pipeline misconfigurations within internal applications and CI/CD systems.
Requirements
5–8+ years in Application Security, Product Security, or Secure Software Development