Cybersecurity Specialist

Job Overview Client • Phoenix, AZ

1d

About The Position

The job overview describes a Senior Engineer-Generative AI Automation who serves as a subject matter expert in Generative AI and agentic engineering. The role builds and operationalizes production-grade autonomous and semi-autonomous AI agents to deliver secure, scalable enterprise automation; integrates agents with enterprise systems and security platforms; and contributes to enterprise security initiatives. The role also supports security champions by promoting security principles and controls. The posting lists the position title as Cybersecurity Specialist, although the overview describes the Senior Engineer-Generative AI Automation role.

Requirements

• Bachelor's degree in Cybersecurity, Data Science, Computer Science, or Software Engineering.
• 10 or more years of experience with automation and development in CI/CD.
• 10 or more years of software engineering experience.
• At least 5 years of cybersecurity experience.
• At least 2 years of Generative AI experience.
• Hands-on experience delivering agentic AI or AI coding-agent solutions into production, preferably in security, developer productivity, or Secure SDLC workflows.
• Experience building production-grade autonomous or semi-autonomous agents, including multi-agent orchestration, tool use, memory management, and prompt engineering.
• Strong expertise in security automation, CI/CD and pull request security integrations, secure-by-design AI architectures, threat modeling, secure code reviews, and vulnerability analysis.
• Proficiency in at least one scripting language: Python, JavaScript, or Bash.
• Familiarity with a compiled language: Go, Rust, or Java.
• Experience with GitHub automation and API integrations.
• Familiarity with database architectures, including Oracle, SQL, and NoSQL databases.
• Strong understanding of OWASP Top 10 and industry best practices in Generative AI security.

Nice To Haves

• Information security certifications such as SANS GIAC, CISSP, or Generative AI certifications are encouraged.
• Experience mentoring teams in application security and secure development practices.
• Master's degree in Cybersecurity, Data Science, Computer Science, or Software Engineering.
• Machine Learning Operations professional certifications.
• Strong knowledge of adversarial robustness techniques and tools for machine learning.
• Strong knowledge of AI risk management frameworks and trustworthy AI practices.
• Experience with agent frameworks and orchestration approaches such as LangGraph, AutoGen, CrewAI, or custom orchestration, and tool-protocol patterns such as Model Context Protocol (MCP).
• Hands-on experience with Anthropic Claude or Claude Code and OpenAI Codex, including prompt and instruction design, tool integration, API/SDK use, evaluation, guardrails, and enterprise adoption patterns.
• Understanding of AI lifecycle management, including model integration, evaluation, and observability.

Responsibilities

• Research emerging threats, vulnerabilities, and technologies to stay current with the evolving security landscape.
• Develop and maintain security automation tooling to improve visibility, enforce security best practices, and streamline processes.
• Automate secure design reviews and integrate security checks into pull request workflows and CI/CD pipelines.
• Design, build, and operationalize agentic AI systems that plan, execute, and adapt across complex workflows.
• Integrate agents with enterprise systems, APIs, data sources, security platforms, and developer tooling.
• Build Secure SDLC agents covering requirements, secure design reviews, threat modeling, code review, dependency and vulnerability analysis, remediation guidance, pull-request checks, and release/security gates.
• Ensure agents enforce least privilege, secrets protection, authorization boundaries, auditability, and approval workflows when interacting with enterprise tools and services.
• Create reusable agent tools, skills, workflows, and orchestration patterns.
• Establish quality and security evaluation practices for agent task success, groundedness, code quality, secure coding, prompt-injection resistance, data leakage, unsafe tool use, permissions, reliability, latency, and cost.
• Apply secure-by-design engineering to AI-assisted development, including sandboxing, policy enforcement, telemetry, observability, traceability, red-team testing, and controls for agent-generated code before merge or deployment.
• Provide technical leadership and mentorship in agent architecture, AI-assisted engineering, secure coding, and production readiness.
• Conduct proof-of-concept work related to security tooling, zero-day vulnerabilities, and emerging risks.
• Support the security champion practice by promoting security principles and controls.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior