DevSecOps & Application Security III

Lancesoft; United States; Remote; USD 110,000 - 117,000; Full time

Job summary

Lancesoft is seeking an Application and AI Security Senior Engineer to reduce security risk across enterprise software development, AI systems, cloud environments, and emerging technologies.

The role focuses on integrating automated security controls into lifecycles, performing SAST/DAST, SCA, SBOM, container scanning, and AI security testing, while partnering with DevOps, cloud, architecture, and governance teams to translate threats into practical, risk-based requirements.

Qualifications

• Bachelor’s degree in Cybersecurity, Computer Science, Information Systems, Engineering, or related discipline, or equivalent professional experience.
• Five or more years of experience in cybersecurity, DevSecOps, Application Security, or related fields.
• Experience with SAST/DAST, SBOM, package/dependency management, container security, and OSS security.

Responsibilities

• Embed automated security controls into technology lifecycles and translate threats into practical, risk-based requirements.
• Collaborate with DevOps, cloud, architecture, and governance teams to secure AI and enterprise systems.

Skills

Cybersecurity

DevSecOps

Application Security

AI Security

Cloud Security

Security Testing

Communication

Education

Bachelor’s degree in Cybersecurity/CS/IS/Engineering

Tools

SAST

DAST

SBOM

CI/CD security

Vulnerability mgmt

Job description

Pay range: $80-85/hr

Description: Position Summary: This is a cybersecurity individual responsible for reducing security risk across enterprise software development, applications, artificial intelligence systems, cloud environments, and emerging technologies. This role combines DevSecOps and Application Security with specialized expertise in AI Security and AI governance enablement. The Application and AI Security Senior Engineer develops and matures scalable security capabilities across the software development lifecycle, including SAST, DAST, software composition analysis, Software and AI-BOM, package and dependency management, container scanning, vulnerability management, and AI red teaming. The position also supports the secure adoption of traditional AI/ML, Generative AI, AIenabled applications, AI agents, agentic systems, coding assistants, models, APIs, Retrieval-Augmented Generation, and AI development platforms. The Application and AI Security Senior Engineer partners with development, DevOps, cloud, architecture, Data & AI, Product Security, and governance teams to embed automated security controls into technology lifecycles and translate emerging threats into practical, risk-based requirements.

Required Experience

• Bachelor’s degree in Cybersecurity, Computer Science, Information Systems, Engineering, or related discipline, or equivalent professional experience.
• Five or more years of experience in cybersecurity, DevSecOps, Application Security, Product Security, software engineering security, cloud security, AI security, or a comparable technical security discipline.
• Demonstrated experience with several Application Security and DevSecOps capabilities, including SAST and DAST, software composition analysis (SCA), SBOM generation and management, Package and dependency management, Container and image scanning, CI/CD and repository security, Open-source software security, Vulnerability management and remediation
• Experience with AI security testing, AI red teaming, Generative AI security, or adversarial testing strongly preferred.

Business Use

• Working knowledge of LLM and GenAI architectures, RAG, agentic systems, model APIs, and associated security considerations - including prompt-injection risks, AI supply-chain security, guardrails, observability, and agent identities and permissions.
• Experience with enterprise cloud, development, container, and AI ecosystems such as Microsoft Azure, Azure DevOps, GitHub Enterprise, GitHub Copilot, Microsoft AI services, Copilot Studio, Azure Databricks, MLflow, AWS, or Google Cloud.
• Experience assessing third-party SaaS, AI services, models, open-source software, development tools, and technology supply-chain components.
• Familiarity with NIST CSF, NIST AI RMF, NIST SSDF, OWASP application and API security, OWASP AI and LLM security guidance, secure development, and threat modeling.
• Relevant certifications such as CISSP, CSSLP, CCSP, GIAC, or cloud security certifications are preferred but not required.
• Strong technical curiosity and the ability to rapidly evaluate unfamiliar technologies, architectures, vulnerabilities, and emerging threats.
• Strong communication skills and ability to interface with technical and nontechnical resources to include senior leaders.
• Ability to distinguish material risks from theoretical concerns and translate technical findings into practical remediation requirements, preventive controls, automation opportunities, and risk-based recommendations