Cybersecurity Specialist

TekWissen•Phoenix, AZ

1d•Hybrid

About The Position

TekWissen’s client is seeking a senior engineer focused on Generative AI automation to support enterprise-wide security initiatives. The position serves as a subject matter expert in Generative AI and agentic engineering, building production-grade agents and automating integrations. The role designs, builds, and operationalizes autonomous AI agents for secure, scalable enterprise automation; helps manage, monitor, and report on Generative AI and agentic AI security risk reduction; and supports the security champion practice by promoting security principles and controls. The specialist builds Secure SDLC agents and security automation that incorporate security throughout software development, from requirements and threat modeling through code review, vulnerability analysis, remediation, pull-request checks, and release gates. Agents must interact securely with enterprise systems and tooling while enforcing least privilege, secrets protection, authorization boundaries, auditability, and approvals. The role also establishes evaluation practices for agent quality and security, applies secure-by-design controls to AI-assisted development, and provides technical leadership and mentorship. This is a six-month temporary assignment in Phoenix, Arizona, with a hybrid work arrangement. The posting identifies the role as “Cybersecurity Specialist,” while the job overview describes the work as Senior Engineer–Generative AI Automation.

Requirements

Bachelor’s degree in Cybersecurity, Data Science, Computer Science, or Software Engineering.
10+ years of experience with automation and development in CI/CD.
10+ 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.
Senior-level experience designing, building, and productionizing autonomous or 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 Anthropic Claude/Claude Code and OpenAI Codex, including prompt and instruction design, tool integration, API/SDK usage, evaluation, guardrails, and enterprise adoption patterns.
Experience building automation tooling for security or developer efficiency.
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.
Strong understanding and experience with OWASP Top 10 and Generative AI security best practices.
Knowledge of agent frameworks such as LangGraph, AutoGen, CrewAI, or custom orchestration.
Understanding of AI lifecycle management, including model integration, evaluation, and observability.
Deep expertise in security automation, CI/CD and pull-request security integrations, secure-by-design AI architectures, and security across the software lifecycle.
Experience with database architectures, including Oracle, SQL, and NoSQL databases.

Nice To Haves

Information security professional certifications, such as SANS GIAC, CISSP, or Generative AI certifications.
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.

Responsibilities

Research emerging threats, vulnerabilities, and technologies to stay current with the security landscape.
Develop and maintain security automation tooling to improve visibility, enforce security 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 plan, execute, and adapt tasks across complex workflows.
Integrate agents with enterprise systems, APIs, data sources, and security platforms.
Build Secure SDLC agents for requirements reviews, 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, enforcing least privilege, secrets protection, authorization boundaries, auditability, and approval workflows.
Create reusable agent tools, skills, workflows, and orchestration patterns using agent frameworks and tool-protocol patterns such as 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 and 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, and translate emerging agent capabilities into scalable enterprise engineering patterns.
Perform proofs of concept related to security tooling, zero-day vulnerabilities, and emerging risks.
Support the security champion practice by promoting security principles and controls.
Help manage, monitor, and report on Generative AI and agentic AI security risk reduction.