Cyber Security Architecture Unit Senior Engineer (Staff)

Əsas vəzifələr Review existing security technologies, tools, and measures to identify gaps and recommend improvements; develop targeted solutions to protect company systems and data against cyberattacks, unauthorized access, and emerging security threats. Lead the end-to-end lifecycle of security systems and tools — from proof-of-concept (PoC) testing and design through implementation and formal handover — ensuring solutions meet both technical and business requirements before go-live. Implement and continuously tune advanced protection policies and configurations within WAF and APM solutions, aligning them with the company's security architecture and risk management strategy; proactively take measures to prevent threats, minimize attack surface, and reduce false positive/negative rates in accordance with evolving business requirements. Design and advocate for Zero Trust architecture principles across network, identity, and application layers; define segmentation strategies, micro-perimeters, and least-privilege access models. Define and govern security architecture for cloud environments (IaaS/PaaS/SaaS), ensuring workload protection, data residency compliance, and alignment with cloud-native security best practices. Author and maintain internal security architecture standards, design principles, and baseline configurations; establish a security review gate ensuring all new systems and features meet architectural requirements before go-live. Identify and mitigate AI-specific threats including prompt injection (direct/indirect), training data poisoning, model extraction, membership inference, and adversarial inputs; apply OWASP Top 10 for LLM Applications and MITRE ATLAS frameworks to assess and manage AI risk across the organization. Ensure integrity of the ML pipeline through artifact signing, model registry governance, dependency and notebook hygiene, and safe handling of model weights; define and enforce a security review gate for AI features prior to launch, along with an acceptable-use standard for AI across the company. ML-Based Detection Engineering — Architect detection capabilities using anomaly detection and clustering techniques for alert triage; maintain realistic operational expectations around false-positive rates, data labeling challenges, and model drift in production security environments. Hands-on experience with LLM guardrail/firewall products and red teaming frameworks (Garak, PyRIT); deep understanding of the Model Context Protocol (client/server model, stdio vs. HTTP transports, trust boundaries) and OAuth-based authorization design for MCP servers — including token scoping and prevention of confused-deputy attacks. Tələblər Higher education in Information Technology, Information/Cybersecurity, Applied Mathematics, Cybernetics, Computer Science, or a related field; a Master’s degree is preferred. Minimum 3 years of experience in cybersecurity or information security, including experience in system administration (Windows/Linux) or network administration. Strong written and verbal communication skills in Azerbaijani and English; Russian is an advantage. Hands-on experience with WAF and application security. Hands-on experience in AI/ML security, including threat modeling for AI systems, securing ML pipelines, and working with LLM security tools. Strong knowledge of cybersecurity best practices, security technologies, and compliance frameworks such as NIST, ISO, GDPR, and PCI-DSS. Understanding of risk management principles and the ability to analyze complex security challenges and develop effective solutions. Experience with cloud and virtualization technologies. Strong project management, communication, teamwork, and stakeholder management skills. Strong decision-making and analytical skills, with a results-oriented mindset and a proactive approach to innovation and continuous self-development. Professional certifications such as CCNA, RHCSA, CySA+, SecurityX, CISSP, CISM, or equivalent are preferred.