Synopsys

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.

You Are

You are a senior security engineer who understands that AI is rapidly changing how enterprises operate, how developers build, and how attackers think. Securing AI means protecting prompts, agents, identities, data flows, model interactions, gateways, RAG pipelines, and the broader ecosystem connecting users, applications, tools, and sensitive enterprise data. You have hands-on experience evaluating and operationalizing emerging AI, GenAI, LLM, agentic AI, and cybersecurity technologies in large enterprise environments. You can take a new AI security technology, assess whether it has real value, build a proof of concept, identify integration challenges, and determine production readiness.

Working across cloud AI platforms like Azure AI Foundry, AWS Bedrock, and Microsoft Copilot Studio is familiar territory. You understand how AI agents authenticate, access data, call tools, interact with enterprise systems, and create new security risks when identity, authorization, observability, and guardrails are not properly designed. You conceptualize security ideas, build high-level designs, validate architectures, automate integrations, and own the path to production. You do not stop at recommendations. You build, deploy, integrate, monitor, and improve solutions that help defend against emerging AI-driven threats.

At Synopsys, you will help build the foundation for secure AI adoption, enabling teams across the company to leverage AI responsibly while reducing risks from data leakage, prompt injection, agent misuse, insecure integrations, weak identity controls, and unmanaged AI adoption.

What You'll Be Doing

• Design, deploy, and integrate AI security technologies including LLM gateways, MCP gateways, prompt guardrails, AI firewalls, AI DLP controls, AI Security Posture Management platforms, and agentic AI security solutions
• Build cybersecurity-focused AI agents and automation workflows that improve risk analysis, executive visibility, security reviews, threat detection, posture management, and operational efficiency
• Develop high-level solution designs and technical architecture patterns for securing GenAI applications, LLM integrations, RAG pipelines, agentic workflows, and cloud-hosted AI services
• Own production deployment of AI security solutions from proof of concept and technical evaluation through architecture review, implementation, operational handoff, and continuous improvement
• Evaluate emerging AI, GenAI, LLM, agentic AI, and cybersecurity technologies including open-source tools, commercial platforms, cloud-native services, and infrastructure automation capabilities
• Deploy and manage AI security controls across cloud AI platforms such as Azure AI Foundry, AWS Bedrock, Microsoft Copilot Studio, and other enterprise AI environments
• Integrate identity and access controls for AI agents, workloads, gateways, and services using Microsoft Entra ID, workload identities, Conditional Access, Privileged Identity Management, and identity governance capabilities
• Design security patterns for agent identity, tool authorization, data access, least privilege, Zero Trust enforcement, and secure agent-to-system communication
• Integrate prompt guardrails, content safety controls, AI DLP, model governance, logging, monitoring, and policy enforcement into AI applications and enterprise AI platforms
• Conduct technical proof of concepts, architecture reviews, vendor evaluations, control validations, and technology selection activities for AI security capabilities
• Partner with cybersecurity, cloud, identity, infrastructure, application development, product security, and business technology teams to embed AI security controls into enterprise solutions
• Automate AI security workflows using Python, APIs, infrastructure automation, orchestration tools, and cloud-native services
• Support the development of reusable AI security patterns, reference architectures, deployment playbooks, and operational standards for enterprise-wide adoption

The Impact You Will Have

• Build the technical foundation for secure enterprise AI adoption by deploying controls that protect users, data, models, agents, and AI-enabled applications
• Strengthen defense against emerging AI threats including prompt injection, data leakage, model misuse, agent manipulation, insecure tool access, and unauthorized data exposure
• Enable cybersecurity teams to leverage AI for automation, risk analysis, posture visibility, security reviews, and executive reporting
• Improve enterprise readiness for agentic AI by establishing secure patterns for identity, access control, data protection, monitoring, and governance
• Accelerate safe AI adoption by providing scalable guardrails that allow teams to innovate without bypassing critical security controls
• Shape the AI security technology stack by evaluating, selecting, and operationalizing platforms that will support enterprise AI security for years to come
• Reduce manual cybersecurity effort by building AI-driven automation, reusable integrations, and production-ready workflows
• Improve visibility into AI risks across cloud platforms, enterprise applications, agents, models, identities, and data flows
• Help establish Synopsys as a secure and responsible adopter of AI technologies across internal operations and customer-facing products

What You'll Need

• 8+ years of hands-on experience in cybersecurity engineering, security architecture, cloud security, application security, security automation, or related technical domains
• Experience evaluating and operationalizing emerging AI, GenAI, LLM, agentic AI, and cybersecurity technologies within large enterprise environments
• Hands-on experience deploying and managing open-source security tools, cloud-native services, commercial security platforms, and infrastructure automation solutions
• Strong understanding of AI security concepts including prompt injection, jailbreak risks, model governance, model security, agentic systems, data lineage, AI risk management, and secure AI design patterns
• Practical experience with LLM gateways, MCP gateways, prompt guardrails, AI firewalls, AI DLP, AI Security Posture Management, or related AI security technologies
• Experience with cloud AI platforms such as Azure AI Foundry, AWS Bedrock, Microsoft Copilot Studio, or similar enterprise AI and agentic AI platforms
• Strong understanding of Identity and Access Management, Zero Trust principles, authentication protocols, authorization models, privileged access, and enterprise identity architectures
• Experience with Microsoft Entra ID, Conditional Access, Privileged Identity Management, Identity Governance, Data Loss Prevention, service principals, managed identities, and workload identities
• Experience with Azure, AWS, or multi-cloud security architectures including identity, networking, data protection, monitoring, governance, and policy controls
• Strong proficiency in Python or similar scripting languages for automation, API integration, data processing, and security workflow development
• Experience conducting proof of concepts, technical evaluations, architecture reviews, control validation, vendor assessments, and technology selection initiatives
• Ability to create high-level designs, reference architectures, deployment plans, operational runbooks, and technical documentation
• Demonstrated ability to own solutions from concept through production deployment with minimal supervision
• Strong communication skills with the ability to explain complex AI security, identity, and cloud risks to technical and non-technical stakeholders
• Experience working cross-functionally with cybersecurity, cloud, infrastructure, application development, product, compliance, and vendor teams
• Industry certification such as Security+, CEH, AWS/Azure AI and security (AZ-900: Microsoft Azure Fundamentals, AI-900: Microsoft Azure AI Fundamentals, Microsoft Cloud and AI Security Engineer Associate), or other relevant cybersecurity certifications is a plus

Who You Are

• You are a builder, not just an advisor. You can take an emerging AI security concept, turn it into a working design, validate it in a proof of concept, and drive it into production
• You are comfortable working in areas where the technology is still evolving. You do not need every standard, framework, or vendor category to be fully mature before you act. You use strong engineering judgment, security principles, and practical testing to make informed decisions
• You understand that identity is central to AI security. You know that every AI agent, workload, gateway, and automation workflow needs the right identity, the right permissions, the right data boundaries, and the right monitoring
• You can evaluate a new AI security vendor and quickly determine whether the product solves a real security problem, integrates with enterprise platforms, and can operate at production scale
• You can work across architecture, engineering, deployment, and operations. You are equally comfortable whiteboarding a design, writing automation scripts, reviewing access models, troubleshooting cloud integrations, and explaining risk to leadership
• You know how to push back when an AI solution introduces unacceptable risk, but you also know how to offer a practical path forward that enables the business to move securely
• You stay current on AI security threats because you understand that the AI attack surface is evolving quickly. You are motivated by the opportunity to build security foundations that help the enterprise adopt AI with confidence

The Team You'll Be Part Of

You will join a newly formed AI Security team of four people, currently based in the US, including an AI Architect, AI Engineers, and AI Security Managers. You will report to a Cyber Security Senior Architect. This role is part of the team's expansion into Greece, and you will work closely with an additional AI Automation Engineer who will join the Athens team. The team operates in a distributed environment across Athens and the US, and you will work hybrid from the Athens office. The team is in build mode, defining AI security architecture, selecting tools, and establishing the security foundation for AI across the enterprise and in products

Rewards and Benefits

We offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non-monetary offerings. Your recruiter will provide more details about the salary range and benefits during the hiring process.

At Synopsys, we want talented people of every background to feel valued and supported to do their best work. Synopsys considers all applicants for employment without regard to race, color, religion, national origin, gender, sexual orientation, age, military veteran status, or disability.