About the Role
The Security Transformation team drives AI-enabled innovation across Cyber Security by developing secure AI platforms, intelligent agents, automation capabilities, and enterprise-scale AI solutions. This role contributes to expanding Ciena's AI ecosystem and accelerating AI adoption across security functions. The position focuses on delivering secure, scalable, and responsible AI solutions that improve cybersecurity outcomes.
How you will make an impact
•Design, build, and operationalize AI-powered applications, copilots, and autonomous agents for cybersecurity use cases.
•Develop Retrieval Augmented Generation (RAG) solutions leveraging enterprise knowledge sources and security data.
•Create MCP-enabled integrations connecting AI agents with security tools, workflows, and enterprise platforms.
•Build secure and scalable AI services using modern software engineering and DevOps practices.
•Enhance self-hosted AI infrastructure, model serving platforms, and AI observability capabilities.
•Develop security automation workflows that improve analyst productivity and reduce operational overhead.
•Partner with Security Operations, Risk, Product Security, Vulnerability Management, and Threat Intelligence teams to deliver AI-driven solutions.
The must haves
•Education: Master's degree OR Bachelor's degree in Computer Science, Artificial Intelligence, Software Engineering, Cyber Security, Data Science, or a related field.
•Experience: 5+ years of software engineering, AI engineering, machine learning engineering, or platform engineering experience.
•Development of Python-based solutions and API-driven architectures.
•Building and deploying production-grade AI applications and services.
•Application of Large Language Models (LLMs), AI agents, prompt engineering, Retrieval Augmented Generation (RAG), vector databases, and semantic search.
•Application of software engineering practices including CI/CD, version control, testing, and code quality processes.
•Analytical troubleshooting, problem solving, communication, and stakeholder management capabilities.
•Experience with self-hosted LLM environments and enterprise AI platforms.
•Experience developing agentic workflows and multi-agent systems.
•Knowledge of AI security risks including prompt injection, model abuse, data leakage, and secure agent design.
Nice to haves
•Experience building AI solutions for cybersecurity use cases.
•Experience with self-hosted LLM environments and enterprise AI platforms.
•Experience developing agentic workflows and multi-agent systems.
•Experience integrating security tools through MCP or API frameworks.
•Knowledge of AI security risks including prompt injection, model abuse, data leakage, and secure agent design.
•Certifications: Microsoft AI Engineer, Azure AI Engineer, AWS ML, CISSP, or related certifications.
