AI Security Architect

HIRING LOCATIONS: Austin-TX or Morrisville-NC

We Are

Synopsys is the leader in engineering solutions from silicon to systems, enabling customers to rapidly innovate AI-powered products. We deliver industry-leading silicon design, IP, simulation and analysis solutions, and design services. We partner closely with our customers across a wide range of industries to maximize their R&D capability and productivity, powering innovation today that ignites the ingenuity of tomorrow.

We are seeking a highly motivated Cybersecurity Architect - AI Security to help define, architect, and secure the next generation of AI-enabled systems, platforms, and services across Synopsys. The Cybersecurity Architect - AI serves as a senior technical leader responsible for developing and implementing security architectures, standards, and governance frameworks for Artificial Intelligence (AI), Generative AI, Agentic AI, Machine Learning (ML), and Large Language Model (LLM) ecosystems.

You Are

You have spent a decade building security into systems that matter, and now you are watching AI reshape everything you thought you understood about attack surface, trust boundaries, and control. You know that securing a model is not the same as securing an application, and securing an autonomous agent is not the same as securing a model. The difference matters, and you have spent the last few years figuring out what that difference actually looks like in production.

You do not wait for frameworks to mature before you act. You read OWASP LLM Top 10, NIST AI RMF, and ISO 42001, then you go build the thing that actually works in your environment. Prompt injection, data poisoning, model theft, these are not buzzwords to you, they are threat vectors you have modeled, tested, and mitigated in real deployments.

You are comfortable walking into a room of GenAI engineers talking about RAG pipelines and vector databases and walking out with a security architecture that does not kill the project but does protect the company. You push back when a design is too open, and you find a way forward when the answer is not obvious. You think in layers, controls, guardrails, and you know that the best security architecture is one that developers can actually use.

At Synopsys, you will shape how a global technology leader secures AI at scale, across products, platforms, and operations that power the semiconductor industry.

What You'll Be Doing

• Design enterprise AI security architecture patterns and reference architectures for GenAI, Agentic AI, ML, and LLM-based systems across cloud, SaaS, on-premises, and hybrid environments
• Conduct AI threat modeling, architecture reviews, and security assessments for AI use cases, evaluating risks related to prompt injection, data poisoning, model theft, model inversion, membership inference, and agent abuse
• Define security standards and implementation patterns for agentic AI platforms, orchestration frameworks, MCP ecosystems, LLM gateways, and autonomous workflows, including policy enforcement, monitoring, logging, and action controls
• Establish controls for secure model training, fine-tuning, deployment, and monitoring, and drive AI red-team and adversarial testing strategies to validate defenses
• Design and implement Agentic Identity and Access Management (IAM) strategy for AI agents, autonomous systems, MCP servers, and AI-enabled applications, including controls for service access, secrets protection, model registries, vector databases, RAG architectures, API security, and data classification
• Led secure AI and model lifecycle initiatives by defining security controls, architectures, and guardrails for AI platforms, agents, and LLM integrations; implementing protections against AI-specific threats; and driving red-team testing and governance to ensure secure, resilient, and trustworthy AI systems.
• Partner with Product Security, Engineering, Cloud, IT, Legal, Privacy, Data Governance, and Enterprise Architecture teams to establish AI security policies, standards, and governance frameworks aligned with NIST AI RMF, ISO 42001, OWASP LLM Top 10, and emerging regulations
• Research emerging AI threats and defensive technologies, evaluate and implement AI Security Posture Management (AI-SPM) tools, and design secure sandbox environments for rapid security evaluation of new AI models, solutions, and agents

The Impact You Will Have

• Shape the enterprise AI security strategy and architecture that enables Synopsys to adopt AI securely, responsibly, and at scale across a global organization
• Reduce risk to intellectual property, customer data, AI models, and critical business processes through practical security guardrails and resilient design patterns that protect what matters most
• Accelerate secure innovation by providing clear, reusable standards for AI, GenAI, Agentic AI, ML, and LLM solutions that engineering and product teams can implement without friction
• Strengthen enterprise readiness for emerging AI threats through threat modeling, adversarial testing, continuous monitoring, and effective detection and response capabilities that adapt as the threat landscape evolves
• Influence executive and cross-functional decisions by translating complex AI security risks into actionable architecture recommendations and mitigation priorities that leadership can act on
• Advance a consistent, security-by-design culture across product, engineering, cloud, IT, legal, privacy, data governance, and enterprise architecture teams, embedding security into AI workflows from the start
• Protect Synopsys customers and partners by securing AI-enabled products and services that power semiconductor design and innovation worldwide

What You'll Need

• Bachelor's degree in Computer Science, Cybersecurity, Engineering, Information Systems, or related field, Master's degree preferred
• 10+ years of experience in Cybersecurity, Security Architecture, Cloud Security, or related disciplines with a track record of building and securing complex systems
• 3+ years of hands-on experience securing AI, Generative AI, LLMs, or ML systems in production environments, not just research or proof-of-concept work
• Deep technical knowledge of AI and ML security, LLM architectures, Agentic AI systems, RAG pipelines, AI model lifecycle security, AI governance frameworks, cloud security architectures, IAM, API security, data security and privacy, secure software development lifecycle, and security monitoring and incident response
• Experience conducting threat modeling, architectural risk assessments, and security design reviews for AI systems, with the ability to identify and mitigate risks like prompt injection, data poisoning, model theft, and agent abuse
• Demonstrated experience working with executive stakeholders and cross-functional teams to drive security strategy, present risk and mitigation recommendations, and influence decision-making at the highest levels
• Strong familiarity with Kubernetes and container security, MLOps and ModelOps platforms, AI orchestration frameworks, vector databases, and the Model Context Protocol (MCP), as well as leading AI ecosystems including Anthropic, OpenAI, NVIDIA AI, Azure OpenAI, AWS Bedrock, and Google Vertex AI.
• CISSP, CCSP, SABSA, TOGAF, or equivalent certifications, GenAI security-related certifications are a strong plus

Who You Are

• You can explain a complex AI security tradeoff to a VP in two sentences without losing the nuance, and then turn around and whiteboard the technical architecture with an AI engineer
• You do not wait for perfect information or fully mature frameworks, you work with what you have, ask the right questions, build what is needed, and iterate as the landscape evolves
• You push back when a design is too open or a risk is being underestimated, and you do it in a way that moves the conversation forward rather than shutting it down

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