Overview

Keysight is at the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization. Our 15,000 employees create world-class solutions in communications, 5G, automotive, energy, quantum, aerospace, defense, and semiconductor markets for customers in over 100 countries. Learn more about what we do.

Our award-winning culture embraces a bold vision of where technology can take us and a passion for tackling challenging problems with industry-first solutions. We believe that when people feel a sense of belonging, they can be more creative, innovative, and thrive at all points in their careers.

Responsibilities

About the Role

Role

We are seeking a highly skilled and experienced Product Security Engineer to design, develop, and scale an AI-driven security automation engine that will integrate directly into Keysight's Software Development Life Cycle (SDLC). This role will lead the development of an intelligent system capable of:

Understanding the full Software Development Life Cycle (SDLC) and shifting left automation of remediation tasks earlier in the SDLC
Consuming and interpreting scan data from our vulnerability assessment platform
Automatically generating exploit and testing scripts using AI
Validating vulnerability existence with high confidence and reproducibility earlier in the SDLC
Feeding verified results back into the UI with reliability, auditability, and traceability
Providing AI-assisted code patching, secure coding recommendations, and CI/CD automation to accelerate mitigation workflows earlier in the SDLC

About The Team

You will collaborate with product owners, security researchers, and full stack engineers to build advanced autonomous security capabilities that enhance Keysight's Software Development Life Cycle (SDLC).

Key Responsibilities

Software Development Life Cycle (SDLC) Integration

Seamlessly integrate security automation into Keysight's Software Development Life Cycle (SDLC)
Enable ingestion, normalization, and correlation across Black Duck SCA, Nessus Vulnerability Management, Burp Suite DAST, SAST tools, and product telemetry

AI-Driven Vulnerability Verification & Automation

Design and implement AI models that interpret vulnerability scan data and autonomously generate exploit scripts
Build automated validation pipelines using sandboxed and orchestrated environments
Develop classification and scoring logic with strong confidence metrics
Implement guardrails, safety classifiers, and auditing for safe LLM operations

False Positive Reduction & Evidence Quality

Build multi‑agent reasoning workflows to reduce false positives
Produce high-fidelity Vulnerability Verification Evidence Packages (VVEP) with logs, traces, and reproducible exploit outcomes

AI Assisted Code Patching & Remediation

Deliver AI-generated secure code recommendations and automated patching workflows
Integrate remediation automation into CI/CD pipelines (Azure DevOps, GitHub Actions, Jenkins)

Penetration Test Augmentation

Support AI-enhanced penetration testing, API fuzzing, and dynamic security validation
Work with security researchers to improve exploit reliability and detection precision

Leadership & Cross Functional Collaboration

Partner with product teams and engineering leadership to ensure validated results drive actionable remediation
Influence secure development practices and drive adoption of security automation across product teams

Qualifications

Must Haves:

Bachelor's degree in Computer Science, Computer Engineering, Cybersecurity, AI/ML, or a related field.
3-6 years of R&D experience, with a strong preference for AI and security‑focused work.
Python proficiency, security automation frameworks, and CI/CD integration.
Experience with secure software development practices and vulnerability management.
Hands-on experience with SAST, DAST, SCA, container scanning, and other security tools.
Familiarity with Git, CI/CD pipelines, build automation, and DevSecOps principles.
Familiarity with LLMs, AI-assisted security workflows, or Agentic AI concepts.
Ability to operate independently and contribute to technical decision-making.
Excellent communication and cross‑team collaboration skills.

We Value

Master's degree in Cybersecurity, Computer Science, or a related technical field.
Hands‑on AI application development experience with exposure to AI/LLMbased verification or autonomous testing frameworks.
Practical experience with AI/ML‑based security automation or Agentic AI/LLM integration (OpenAI, Azure OpenAI, HuggingFace).
Exposure to cloud security or container/Kubernetes security for software development pipelines.
Experience with penetration‑testing methodologies (OWASP, PTES, MITRE ATT&CK).
Understanding of vulnerability types (CVE/CWE), exploit vectors, and modern attack techniques.
Experience with multitool security data environments (SAST + DAST + SCA + VM).
Experience producing SBOM, VEX, VVEP, or SARIF artifacts.
Working knowledge of Docker, Kubernetes, and modern CI/CD platforms.
Background in fuzzing, exploit development, or dynamic testing automation.
Experience integrating tooling into CI/CD systems.
A passion for continuous improvement and learning.
Excellent problem-solving skills and attention to detail.
Proven ability to work cross-functionally and influence without authority.

Careers Privacy Statement***Keysight is an Equal Opportunity Employer.***

Product Security Engineer Security & Agentic AI