AI Security Software Engineer

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AI Security Software Engineer

Location: This role requires associates to be in-office 1 - 2 days per week, fostering collaboration and connectivity, while providing flexibility to support productivity and work-life balance. This approach combines structured office engagement with the autonomy of virtual work, promoting a dynamic and adaptable workplace. Alternate locations may be considered if candidates reside within a commuting distance from an office.

Please note that per our policy on hybrid/virtual work, candidates not within a reasonable commuting distance from the posting location(s) will not be considered for employment, unless an accommodation is granted as required by law.

PLEASE NOTE: This position is not eligible for current or future visa sponsorship.

The AI Security Software Engineer designs, develops, and implements AI-driven security solutions to assess enterprise applications, analyze source code, and identify vulnerabilities. This role combines software engineering, application security, DevSecOps, and large language model (LLM) technologies to strengthen security capabilities, automate assessments, and reduce enterprise risk.

• Design, develop, test, and maintain AI-enabled application security solutions and automated vulnerability assessment capabilities.
• Build and integrate security assessment pipelines that combine traditional security scanning tools with AI-assisted source code analysis and vulnerability identification.
• Develop integrations with source code repositories, security tools, vulnerability management platforms, enterprise workflows, and AI/LLM platforms.
• Lead the design and implementation of DevSecOps solutions, embedding security controls, automated testing, and secure coding practices into CI/CD pipelines.
• Define technical requirements, system architecture, and reusable integration frameworks supporting AI models, security tools, and assessment engines.
• Establish security guardrails for AI-generated code and AI-enabled applications, addressing risks such as prompt injection, insecure code, sensitive data exposure, and model misuse.
• Lead security risk assessments, vulnerability prioritization, and remediation strategies aligned with business, regulatory, and technical requirements.
• Develop security metrics and reporting to measure security posture, assessment coverage, and risk reduction.
• Collaborate with application security, penetration testing, software engineering, AI engineering, and platform teams to deliver scalable security solutions.
• Serve as a technical subject matter expert, providing guidance, troubleshooting complex issues, and supporting security incident response strategies.

Requires BS/BA in information Technology or related field of study and a minimum of 8 years experience in systems administration and security aspects of information systems, access management and network security technologies, network communications, computer networking, telecommunications, systems development and management, hardware, software, data, and people; experience with multiple technical and business disciplines required; or any combination of education and experience, which would provide an equivalent background.

• Software Engineering: Strong Python development skills, including experience building REST APIs using FastAPI, Flask, Django, or similar frameworks. Familiarity with asynchronous processing, concurrency, automated testing (pytest), and SQL databases.
• AI/LLM Integration: Experience developing AI-enabled or agent-based systems using commercial or open-source LLMs, prompt engineering, tool calling, structured outputs, context management, and enterprise AI platforms.
• Application Security: Strong knowledge of OWASP Top 10, CWE, SAST, DAST, SCA, API security, secrets detection, software supply chain security, and vulnerability assessment.
• AI Security: Experience securing AI/LLM applications and AI-assisted development workflows, including mitigating prompt injection, data leakage, insecure tool use, excessive agency, and untrusted code execution.
• DevSecOps & CI/CD: Hands-on experience integrating security into CI/CD pipelines using GitHub, GitLab, Jenkins, Azure DevOps, Bitbucket, or similar platforms.
• Cloud & Container Security: Knowledge of AWS, Azure, or GCP, container security, Kubernetes, and modern cloud deployment practices.
• Security Tool Integration: Experience integrating application security and vulnerability management platforms, including vulnerability correlation, deduplication, prioritization, risk scoring, and standardized formats such as SARIF.
• AI Evaluation & Testing: Familiarity with model evaluation techniques, including labeled datasets, precision/recall metrics, regression testing, and comparative model analysis.
• Development & Observability: Experience with Git-based development, code reviews, automated testing, logging, metrics, distributed tracing, and production monitoring.
• Additional Technologies: Familiarity with React, JavaScript, TypeScript, enterprise workflow platforms, and IT service management systems.
• Enterprise Security & Communication: Experience in regulated or security-sensitive environments, with strong technical documentation, architecture design, and stakeholder communication skills.
• Certifications: Security certifications such as CSSLP, OSWE, GWEB, cloud security certifications, or equivalent are strongly preferred.

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