Cybersecurity Specialist

Job Overview


Client is seeking Senior Engineer-Generative AI Automation with proven strong technical competence and leadership capability to contribute towards the success of enterprise-wide Security initiatives. Senior Engineer-Generative AI Automation serves as a subject matter expert in Generative AI and agentic engineering, with hands-on experience building production-grade agents using platforms and coding agents such as Anthropic Claude/Claude Code and OpenAI Codex, automates integrations and plays an integral role in managing, monitoring & reporting on Generative AI, Agentic AI security risk reduction, design, build, and operationalize autonomous AI agents that drive secure, scalable, and intelligent automation across the enterprise and supports the security champion practice by evangelizing security principles and controls.


Primary Responsibilities
• Experience building automation tooling for security or developer efficiency
• Proficiency in at least one scripting language (Python, JavaScript, or Bash) and familiarity with a compiled language (Go, Rust, or Java)
• Experience with GitHub automation and API integrations. Conduct research on emerging threats, vulnerabilities, and technologies to stay updated on the evolving security landscape.
• Develop and maintain security automation tooling to enhance 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 and develop agentic AI systems that autonomously plan, execute, and adapt tasks across complex workflows
• Integrate agents with enterprise systems, APIs, data sources, and security platforms
• Strong understanding, experience with OWASP Top10 and industry best practices within Generative AI security.
• Knowledge of agent frameworks (e.g., LangGraph, AutoGen, CrewAI, custom orchestration)
• Understanding of AI lifecycle management, including model integration, evaluation, and observability
• Demonstrated senior-level experience designing, building, and productionizing autonomous and semi-autonomous AI agents, including planning, tool use, memory/context management, multi-agent orchestration, human-in-the-loop controls, and failure recovery.
• Hands-on experience with leading AI coding and agent platforms such as Anthropic Claude/Claude Code and OpenAI Codex, including prompt/instruction design, tool integration, API/SDK usage, evaluation, guardrails, and enterprise adoption patterns.
• Build Secure SDLC agents that embed security across the software lifecycle, including requirements and secure design review, threat modeling, code review, dependency and vulnerability analysis, remediation guidance, pull-request checks, and release/security gates.
• Design agents that securely interact with source control, CI/CD, issue tracking, security scanners, cloud services, internal APIs, and developer tooling while enforcing least privilege, secrets protection, authorization boundaries, auditability, and approval workflows.
• Experience creating reusable agent tools, skills, workflows, and orchestration patterns using frameworks such as LangGraph, AutoGen, CrewAI, custom orchestration, and tool-protocol patterns such as Model Context Protocol (MCP).
• Establish agent quality and security evaluation practices covering 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 for agent architecture, AI-assisted engineering, secure coding, and production readiness; translate emerging agent capabilities into scalable enterprise engineering patterns.
• Experience performing POC's regarding security tooling, zero-day vulnerabilities and emerging risks.
• Familiarity with database architectures: Oracle, SQL and NoSQL Databases.
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Desired Skills
• Information security professional certifications encouraged, such as SANS GIAC, CISSP, Generative AI certifications.
• Experience mentoring application security and secure development practices to the team.
• Master's Degree - Cyber Security, Data Science, Computer Science, or Software Engineering
• Machine Learning Operation Professional Certifications.
• Strong knowledge of Adversarial Robustness techniques and tools for machine learning.
• Strong knowledge of AI Risk Management frameworks and Trustworthy AI practices.
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Minimum Qualifications
• Bachelor's degree in Cybersecurity, Data science, Computer Science or Software Engineering.
• 10 + years' experience with Automation and Development in CI/CD.
• 10+ years of software engineering experience.
• 5+ Years of Cybersecurity.
• 2+ years of Generative AI experience.
• Hands-on experience delivering agentic AI or AI coding-agent solutions into production, preferably within security, developer productivity, or Secure SDLC workflows.
• Generative AI & Agentic Engineering: Hands-on experience building production-grade autonomous/semi-autonomous agents using platforms and frameworks like Anthropic Claude/Claude Code, OpenAI Codex, LangGraph, AutoGen, CrewAI, and Model Context Protocol (MCP), covering multi-agent orchestration, tool use, memory management, and prompt engineering.
• Security Automation & Secure SDLC: Deep expertise in developing security automation tooling, integrating security checks into CI/CD pipelines and pull request workflows, designing secure-by-design AI architectures, and embedding security across the software lifecycle (threat modeling, secure code reviews, and vulnerability analysis).
• Software Engineering & Scripting Proficiency: Strong foundational background in software development with proficiency in at least one scripting language (Python, JavaScript, or Bash), familiarity with compiled languages (Go, Rust, or Java), and experience with GitHub automation, API integrations, and database architectures.