Network Security (Temp Contract)

Requirements

• Education / Experience
• Solid Security Foundation: Minimum 5 years of experience in Cybersecurity, with deep knowledge of network security principles (NAC, Firewalls, ZTNA).
• Innovation Track Record: Proven experience leading technical workstreams from concept to production, particularly those involving new technology adoption.
• Scale & Scope: Proven experience in architecting and operating solutions at a global scale.
• Educational Background: Bachelor's degree in Computer Science, Data Science, Cyber Security, Information Technology, or a related technical field.
• Technical Skills
• AI/ML Proficiency: Practical experience applying AI/ML concepts (e.g., Supervised/Unsupervised learning, NLP, or Anomaly Detection) to technical datasets.
• Programming & Data Science: Proficiency in Python and experience with API-driven integrations.
• Security Platforms: SME-level understanding of Cisco ISE, 802.1x, and Palo Alto Networks (Pan-OS, Panorama).
• Cloud & Big Data: Familiarity with cloud-based AI services (AWS SageMaker, Azure ML) and processing large-scale se

Benefits

Additional Information

At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections, where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters. The Position The Network Security product makes Roche's connectivity accessible and secure through actionable, policy-driven processes. The capabilities we provide enable Roche to identify, inspect, and mitigate network-based risks, manage regulatory compliance, and oversee egress/ingress traffic across all layers. Our solutions are primarily instantiated through leading-edge security platforms and automated orchestration. We work closely with Cloud, Infrastructure, and Incident Response teams to provide enterprise visibility into Roche's network security posture. You'll be working within the Network Security Product area. This area is accountable for the end-to-end delivery of solutions-designing, building, and maintaining the technologies that protect Roche networks and the Internet, whether on-prem or cloud-based. This includes continuous improvement of capabilities like Internet Security Stack, DDoS Protection , Site-to-Site Connectivity (VPN) , Network Access Control and Deep Packet Inspection to stay ahead of an ever-evolving threat landscape. Job Description As a Cybersecurity Engineer within the AI Innovation workstream, you will be a key technical contributor responsible for the hands-on execution of our AI/ML security strategy. Working as part of a specialized team, you will assist in developing and implementing AI capabilities to optimize service delivery across the Design, Build, and Operations phases of our network security solutions. Your role is to help bridge the gap between network security engineering and data science, contributing to the development of intelligent automation that reduces manual intervention and shifts our infrastructure toward a proactive, self-healing model. You will apply your technical expertise to ensure these technologies integrate seamlessly with our core stack, including Cisco ISE, 802.1x, and Palo Alto Networks. Job Responsibilities 1. AI Strategy & Roadmap Execution Strategy Definition: Partner with product owners to define the vision for AI adoption within Network Security (e.g., predictive threat detection, automated policy optimization). Hands-on Implementation: Lead the technical execution of AI workstreams, moving from Proof of Concept (POC) to production-ready security enhancements. SME for AI Security: Act as the Subject Matter Expert for how AI can be leveraged to improve the efficacy and performance of Cisco ISE, Palo Alto, and 802.1x infrastructures. 2. AI-Driven Observability & Inventory Intelligent Monitoring: Develop AI/ML models to identify anomalies in network traffic and security appliance telemetry that traditional threshold-based monitoring misses. Automated Classification: Enhance asset inventory and device profiling (NAC) by applying machine learning to identify complex IoT and medical device patterns. Framework Integration: Integrate AI insights into the existing observability front-end and backend frameworks to provide actionable intelligence to operations teams. 3. Proactive Defense & Automation Predictive Analytics: Implement tools to predict potential security bottlenecks or infrastructure failures before they impact the global network. Policy Optimization: Use AI to analyze firewall and NAC policy usage, recommending automated cleanup or hardening of security rules. Continuous Improvement: Lead the "Design, Build, and Improve" cycle for AI-driven security controls, ensuring they evolve alongside the threat landscape.

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