Cybersecurity Specialist

TekWissen•Phoenix, AZ

1d•Hybrid

About The Position

TekWissen is seeking a Cybersecurity Specialist for a six-month temporary assignment in Phoenix, Arizona. The posting describes the work as hybrid and also refers to the role as Senior Engineer-Generative AI Automation. The position contributes technical expertise and leadership to enterprise-wide security initiatives, with a focus on Generative AI and agentic engineering. The role builds and operationalizes production-grade autonomous and semi-autonomous AI agents, automates integrations, and supports the management, monitoring, and reporting of AI security risk reduction. It also supports the security champion practice by promoting security principles and controls. The role combines security automation, software engineering, and agentic AI development. It builds Secure SDLC agents and integrates security into software delivery workflows, including requirements and design reviews, threat modeling, code review, dependency and vulnerability analysis, remediation guidance, pull-request checks, and release gates. Agents must interact securely with enterprise systems and tools, with appropriate least-privilege access, secrets protection, authorization boundaries, auditability, and approval workflows. The position also establishes quality and security evaluation practices for agents; applies secure-by-design controls such as sandboxing, policy enforcement, telemetry, traceability, and red-team testing; and provides technical leadership and mentorship on agent architecture, AI-assisted engineering, secure coding, and production readiness. The posting notes experience with security tooling proofs of concept, zero-day vulnerabilities, emerging risks, and database architectures.

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.
5+ years of cybersecurity experience.
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 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 of OWASP Top 10 and industry best practices in Generative AI security.
Demonstrated senior-level experience designing, building, and productionizing autonomous and semi-autonomous AI agents, including planning, tool use, memory and context management, multi-agent orchestration, human-in-the-loop controls, and failure recovery.
Hands-on experience with Anthropic Claude or Claude Code and OpenAI Codex, including prompt and instruction design, tool integration, API or SDK usage, evaluation, guardrails, and enterprise adoption patterns.
Understanding of AI lifecycle management, including model integration, evaluation, and observability.
Experience creating reusable agent tools, skills, workflows, and orchestration patterns using frameworks such as LangGraph, AutoGen, CrewAI, custom orchestration, and MCP.
Familiarity with Oracle, SQL, and NoSQL database architectures.

Nice To Haves

Information security professional certifications are encouraged, 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 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.

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, develop, and operationalize autonomous and semi-autonomous AI agents for secure enterprise automation.
Integrate agents with enterprise systems, APIs, data sources, security platforms, source control, CI/CD, issue tracking, security scanners, cloud services, internal APIs, and developer tooling.
Build Secure SDLC agents that support requirements and secure design reviews, threat modeling, code review, dependency and vulnerability analysis, remediation guidance, pull-request checks, and release or security gates.
Ensure secure agent interactions through 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 practices 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.
Conduct proofs of concept involving security tooling, zero-day vulnerabilities, and emerging risks.
Provide technical leadership and mentorship in agent architecture, AI-assisted engineering, secure coding, and production readiness.
Translate emerging agent capabilities into scalable enterprise engineering patterns.
Support the security champion practice by promoting security principles and controls.
Automate integrations and contribute to managing, monitoring, and reporting on Generative AI and Agentic AI security risk reduction.