Remote — open to applicants worldwide.
The Application Security Lead Engineer is a mid-level role focused on strengthening application and cloud security practices across engineering environments. This position centers on applying Cloud Security, DevSecOps, and AI/ML security capabilities at an established working level to support secure software delivery. The role contributes directly to reducing security risk and improving how security is built into development workflows.
• Cloud Security — target L6 (Prof), must-have • DevSecOps — target L6 (Prof), must-have • AI/ML security — target L6 (Prof), must-have • Python — target L6 (Prof), nice-to-have • Java — target L6 (Prof), nice-to-have • microservices — target L6 (Prof), nice-to-have • Kubernetes — target L6 (Prof), nice-to-have • Working AI leverage — observed and scored, never assumed • 6–12 years of relevant experience From the hiring team: Required Skills & Qualifications • 6 years of relevant experience in Application Security, AppSec engineering, Cloud Security, or Software Engineering • Deep expertise in application security, secure software design, and risk management, including frameworks such as OWASP ASVS, OWASP Top 10, and NIST 800 53. • Extensive experience conducting complex security assessments and building automated security controls for large engineering environments. • Proficiency in multiple programming languages (e.g., Python, Java, JavaScript) and hands-on experience with SAST, DAST, SCA, IaC, container, and cloud security tools. • Strong understanding of modern architectures (cloud-native, microservices, Kubernetes, containers, serverless) and DevSecOps processes. • Advanced understanding of AI/ML security, including model vulnerability analysis, AI threat modeling, secure LLM integration patterns, and familiarity with NIST AI RMF or OWASP Top 10 for LLMs
Support application security efforts across software delivery and cloud-based environments. Apply DevSecOps practices to help embed security into development workflows and engineering processes. Contribute AI/ML security expertise to help address security considerations in systems that involve AI or machine learning. Work across application and platform contexts where Python, Java, microservices, and Kubernetes may be part of the technical environment.
Techies4tech.ai is an organization with client details not specified.
This role offers the opportunity to work at the intersection of application security, cloud security, and DevSecOps in a position with direct impact on engineering practices. It is also a chance to contribute to AI/ML security as part of the role’s core scope, supporting secure delivery in an area of growing importance.
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