Cyber Security Engineer

Job Title: GDS Cyber - Frontier AI Layered Defense Detection and Response - Senior

Senior Cybersecurity Engineer Agentic AI & SOC Engineering (4–7 Years)

Role Overview

As a Senior Cybersecurity Engineer, you will help build next-generation SOC solutions by combining SIEM/XDR/SOAR with AI/LLM-driven automation. The role focuses on designing agent-based AI systems to enhance threat detection, automate investigations, and orchestrate response actions, while engaging in both hands-on engineering and client delivery.

Key Responsibilities

• Design and implement agentic AI-driven SOC architectures integrated with SIEM, XDR, and SOAR
• Develop AI use cases for alert triage, investigation, incident summarization, and automated response
• Build and optimize detection use cases using rule-based and AI-assisted approaches
• Integrate LLM capabilities into SOC workflows (analysis, correlation, playbooks)
• Support platform deployment, migration, and tuning across SIEM/XDR environments
• Improve SOC efficiency through automation, noise reduction, and prioritization
• Operationalize threat intelligence into detection pipelines
• Collaborate with clients on solution design and implementation
• Create architecture diagrams, playbooks, and technical documentation
• Contribute to AI-driven SOC capability building

Required Skills & Experience

• 4–7 years in Cybersecurity / SOC Engineering / Detection & Response
• Experience with platforms such as Microsoft Sentinel, Defender XDR, CrowdStrike, or Splunk
• Strong understanding of SIEM, SOAR, XDR/EDR, and detection engineering
• Exposure to AI/ML or LLM use cases in SOC environments
• Experience with automation (playbooks, APIs, scripting)
• Familiarity with prompt engineering or AI-assisted workflows
• Knowledge of MITRE ATT&CK and incident response lifecycle
• Strong problem-solving and client communication skills

Preferred Skills

• Experience with agentic AI frameworks (LangChain, Semantic Kernel, AutoGen, etc.)
• Exposure to Azure AI / OpenAI platforms
• Understanding of RAG, embeddings, or semantic search
• Experience integrating AI into SOC use cases (correlation, copilots, auto-remediation)
• Knowledge of cloud security / DevSecOps