AI Security & DevSecOps Specialist

Fluor Corporation

Greenville (SC)

On-site

USD 83,000 - 154,000

Full time

14 days+

Application generator

Turn this role into an interview — a resume and cover letter built around what this employer wants.

Get past ATS filters

Job summary

Fluor Corporation is seeking an AI Reviews / DevSecOps Specialist to ensure secure delivery of AI-enabled solutions by performing security reviews and governance documentation. The role collaborates with Security Operations, AI Security and Privacy Architecture, developers, and platform teams to embed secure practices into delivery workflows.

The position requires expertise in AI security, application security reviews, and DevSecOps controls, with a focus on risk reduction and defensible

Qualifications

Accredited four (4) year degree or global equivalent in applicable field of study and five (5) years of work-related experience or a combination of education and directly related experience equal to nine (9) years if non-degreed; some locations may have additional or different qualifications in order to comply with local requirements
Ability to communicate effectively with audiences that include but are not limited to management, coworkers, clients, vendors, contractors, and visitors
Job related technical knowledge necessary to complete the job
Ability to learn and apply knowledge of applicable local, state/province, and federal/national statutes and guidelines
Ability to attend to detail and work in a time-conscious and time-effective manner

Responsibilities

Perform security reviews for AI-enabled applications, copilots, agents, integrations, and supporting APIs before production deployment
Execute AI-specific security checks, including prompt-injection testing, jailbreak resistance review, tool-misuse assessment, sensitive-data leakage testing, grounding/source validation, and abuse-case review
Review remediation plans, validate fixes, and document residual risk, compensating controls, or waiver/risk-register inputs when required
Partner with development and platform teams to embed secure coding, threat modeling, CI/CD security gates, SBOM/SCA review, and secure deployment practices into delivery workflows
Assess third-party and internally developed AI solutions for data handling, access control, logging, retention, model interaction, and integration risks
Maintain reusable review checklists, evidence templates, testing playbooks, and operating procedures for AI and application security assessments
Stay current with AI security threats, application vulnerabilities, OWASP guidance, and DevSecOps tooling trends, and translate lessons learned into practical review criteria