TERADYNE, where experience meets innovation and driving excellence in every connection. We are fueled by creativity and diversity of thought and in our workforce. Our employees are challenged to innovate and learn something new every day.
We cultivate a culture of inclusion for all employees that respects their individual strengths, views, and experiences. We believe that our differences enable us to be a better team – one that makes better decisions, drives innovation and delivers better business results.
Overview
Teradyne is building dedicated, in-house AI security engineering capability within the Information Security organization to keep pace with the rapid adoption of AI agents, large language models (LLMs), and AI-enabled tooling across the enterprise. As AI becomes embedded in how the company operates, from everyday productivity tools to autonomous agents to security operations itself, Teradyne needs an engineer who can both lock down how AI is used across the enterprise and put AI to work strengthening our own cyber defenses. The AI Security Engineer owns both halves of that mission.
Securing AI Across the Enterprise: This role secures the use of third-party and internally deployed AI tools across Teradyne, ensuring sensitive data, intellectual property, and engineering workflows are protected as AI becomes deeply embedded in how work gets done.
Leading the Evolution of AI Cybersecurity Defense: This role also leads the evolution of AI cybersecurity defense and AI-driven security automation, shaping how Teradyne's security operations and solutions leverage AI to detect, investigate, and respond to threats at scale.
This role sits within the Information Security organization and works closely with the Deputy CISO, Product Security, and the broader AI Transformation program to ensure new AI investments (including enterprise platforms already in use such as Microsoft Copilot and Claude, as well as internally built agents) are secure by design and aligned to frameworks such as the NIST AI Risk Management Framework (AI RMF) and Teradyne's AI Cyber Operational Capabilities Framework.
The ideal candidate combines strong security engineering fundamentals with hands-on experience testing and securing modern AI systems, including LLMs, autonomous agents, and the protocols and tooling that connect them (e.g., MCP-based integrations), and brings an automation-first mindset to reduce manual effort and strengthen detection and response across the security program.
Responsibilities
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Enterprise AI Security: Define and implement security controls and guardrails for the use of AI tools (LLM APIs, SaaS AI platforms, internal AI services, and agents) across the organization, including AI/agentic gateway controls that manage and monitor access and enforce identity, authorization, and tool-use constraints for autonomous or semi-autonomous agents.
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AI Security Platform Ownership: Own, operate, and continuously improve Teradyne's AI security solutions and platforms, including AI/agentic gateways, AI-aware monitoring, and enterprise AI security tooling, keeping capabilities current, well-configured, and effective against the latest AI and agentic threats as the technology and threat landscape evolve.
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Data Protection for AI Usage: Develop and enforce controls to prevent sensitive data and IP leakage through AI systems, including input/output filtering, data classification, and secure handling of prompts, embeddings, and outputs, integrated with Teradyne's existing DLP tooling and processes.
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AI Threat Modeling: Develop threat models for new and existing AI use cases, identifying risks such as data leakage, prompt injection, model misuse, supply-chain risk from AI vendors, and unauthorized agent actions.
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AI Security Reviews & Architecture: Own AI-related security reviews within the architecture review process, defining controls for agent identity, tool/API access, data-use constraints, and auditability, and acting as the security gate for new AI projects, agents, and integrations before they reach production.
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Vendor & Platform Security: Evaluate third-party AI vendors and platforms (e.g., Copilot, Claude, LLM APIs, other SaaS AI tools) for data handling practices, model behavior, and integration risk, favoring proven commercial AI security capabilities over custom builds where practical.
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Security Enablement: Contribute to internal guidance and education on safe AI usage, including secure prompting, data handling, and appropriate use of AI tools.
Leading AI Cybersecurity Defense & Automation
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AI-Driven Security Automation: Lead the evolution of AI-enhanced cybersecurity defense, applying AI and agentic approaches to detection engineering, automated response, threat hunting, and broader security automation.
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Tooling & Automation: Build and maintain automation (playbooks, scripts, and AI-assisted tooling) that reduces manual effort across security operations and incorporates AI-aware detections into Teradyne's existing security stack (SIEM, SOAR, DLP, EDR).
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Incident Response for AI-Related and AI-Assisted Cases: Serve as a technical resource for security incidents involving AI systems (e.g., sensitive data exposure via AI tools, compromised API keys, agent misuse), and apply AI-driven tooling to accelerate investigation and response for security incidents more broadly.
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Attack Simulation: Build and automate realistic attack simulations and adversary emulation scenarios to continuously validate detection and response capability.
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Frameworks & Standards: Track and apply emerging AI security and defense frameworks and guidance, including the NIST AI RMF, MITRE ATLAS, and OWASP guidance for LLM applications, to keep internal practices current, and contribute technical evidence to support internal and third-party AI security assessments and audits.
Cross-Cutting
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Cross-Functional Collaboration: Partner with the AI Transformation program, Product Security, Enterprise Architecture, Legal, and Compliance to align AI usage and AI-driven defense capabilities with regulatory requirements, data governance policies, and responsible AI practices.
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Documentation: Document AI security standards, playbooks, and review criteria as Teradyne's AI usage and AI-driven defense capabilities mature.
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Perform other duties as assigned.
Qualifications
Required
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Bachelor's degree in Computer Science, Information Security, Engineering, or a related field, or an equivalent combination of education and demonstrated experience.
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5-7+ years of experience in security engineering, application security, or another hands-on technical security role.
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Working knowledge of how large language models, AI agents, and agent-to-tool integrations (e.g., MCP-style protocols) function, including common security weaknesses such as prompt injection, jailbreaks, data/model poisoning, and unsafe autonomy.
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Familiarity with how enterprise AI platforms in active use at Teradyne (such as Microsoft Copilot, Claude, and other LLM or agent tools) are typically deployed, governed, and secured.
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Familiarity with security operations concepts (detection engineering, threat hunting, incident response) and how AI and automation can be applied to strengthen them.
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Experience with security testing techniques such as penetration testing, vulnerability assessment, and threat modeling, and the ability to apply them to novel AI and agentic systems.
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Proficiency in at least one modern scripting or programming language (e.g., Python) for building security automations and tooling.
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Familiarity with cloud platforms, CI/CD pipelines, and API-based integrations, and how to secure them.
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Strong analytical and problem-solving skills with the ability to work through ambiguity, given how new and fast-moving AI security practices are.
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Clear communicator, able to translate technical AI security findings into guidance for engineers, architects, and leadership.
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Self-directed and comfortable operating within a small, growing team and evolving processes.
Preferred
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Experience building or integrating AI-driven or agentic approaches into security automation, orchestration, or SOAR-style tooling and playbook development.
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Familiarity with AI orchestration and agent frameworks (e.g., LangChain, Semantic Kernel, LlamaIndex) or MCP-based agentic tooling.
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Familiarity with the NIST AI Risk Management Framework (AI RMF), MITRE ATLAS, OWASP guidance for LLM applications, and related AI governance and compliance frameworks (e.g., ISO 42001).
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Familiarity with Microsoft/Azure AI security controls (e.g., Azure OpenAI, Microsoft Entra ID, Azure AI Foundry), given Teradyne's Microsoft-centric environment.
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Experience evaluating third-party AI vendor security posture (e.g., SOC 2 / ISO reports, penetration test summaries) to support buy-versus-build decisions.
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Experience with DLP, EDR/XDR, or SIEM platforms.
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Relevant security certifications (e.g., OSCP, GIAC, CISSP) or AI-security-focused training or certifications.
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Experience working within a distributed or offshore team model, collaborating across time zones with a US-based security leadership team.
We are only considering candidates local to position location and are unable to provide relocation for this position.
This position is not eligible for visa sponsorship.
Benefits
Teradyne offers a variety of robust health and well-being benefit programs, insurance, paid vacation & holidays, tuition assistance programs, and more.
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