GDS Cyber - Frontier AI Layered Defense Detection and Response - Manager

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CDR - Manager – Agentic AI SOC Transformation

Experience: 8–12 Years

Role Overview

As a Manager in Agentic AI SOC Transformation, you will lead enterprise clients in evolving their traditional SOC into an intelligent, AI-driven, agent-enabled security operations model.

This role combines SOC strategy, platform engineering, and applied AI leadership, with a strong focus on designing and operationalizing agentic AI use cases across SIEM, SOAR, and XDR ecosystems. You will oversee end-to-end transformation programs—spanning assessment, architecture, implementation, and optimization—while managing client stakeholders and internal delivery teams.

You will play a critical role in bridging cybersecurity operations and AI innovation, ensuring solutions are practical, scalable, and aligned to real-world SOC challenges.

Key Responsibilities

• Client Engagement & Transformation Leadership
  
  
  
  • Lead SOC transformation programs with a focus on Agentic AI adoption
  
  
  • Define target operating models for AI-enabled SOCs (people, process, technology)
  
  
  • Conduct maturity assessments and develop transformation roadmaps
  
  
  • Engage with client leadership (CISOs, SOC heads) to align on strategy, value, and outcomes
  
  
  
  

• Solution Architecture & Delivery
  
  
  
  • Architect agentic AI-driven SOC solutions integrating SIEM, SOAR, XDR, and AI platforms
  
  
  • Design and oversee implementation of AI agents for SOC use cases, such as:
    
    
    
    • Alert triage and prioritization
    
    
    • Investigation copilots and enrichment
    
    
    • Incident summarization and reporting
    
    
    • Automated response orchestration
    
    
    
    
  
  
  • Ensure integration of LLMs, RAG pipelines, and contextual data sources into SOC workflows
  
  
  • Guide teams on platform deployment, migration, and optimization initiatives
  
  
  
  

• AI-Driven SOC Innovation
  
  
  
  • Identify and implement high-impact AI use cases to improve SOC efficiency and detection quality
  
  
  • Drive adoption of agentic workflows and multi-agent orchestration patterns
  
  
  • Establish best practices for prompt engineering, context management, and AI governance
  
  
  • Balance AI automation with analyst decision-making for effective outcomes
  
  
  
  

• Team Leadership & Delivery Management
  
  
  
  • Lead cross-functional teams of SOC engineers, detection engineers, and AI specialists
  
  
  • Provide technical guidance and mentorship on AI-integrated SOC workflows
  
  
  • Ensure high-quality delivery across projects, including timelines, documentation, and outcomes
  
  
  • Support capability building and internal knowledge development in Agentic AI security
  
  
  
  

• Stakeholder Communication & Thought Leadership
  
  
  
  • Lead client workshops, demos, and executive presentations
  
  
  • Translate technical concepts into business outcomes and ROI-driven narratives
  
  
  • Contribute to thought leadership, solution accelerators, and reusable frameworks
  
  
  
  

Required Skills & Experience

• 8–12 years in Cybersecurity / SOC Engineering / Detection & Response, with leadership experience


• Strong expertise in SIEM, SOAR, and XDR platforms (e.g., Microsoft Sentinel/Defender, CrowdStrike, Splunk)


• Proven experience in SOC transformations, platform implementations, or large-scale deployments


• Hands-on or applied understanding of AI/LLM use cases in cybersecurity


• Experience integrating automation, APIs, and orchestration workflows in SOC environments


• Strong understanding of threat detection, incident response, and MITRE ATT&CK framework


• Ability to manage client stakeholders and drive strategic conversations

Preferred / Good-to-Have

• Experience with agentic AI frameworks (e.g., LangChain, Semantic Kernel, AutoGen, etc.)


• Exposure to Azure OpenAI, AI platforms, or cloud-native AI services


• Understanding of RAG architectures, embeddings, and semantic search


• Experience designing AI copilots or automation solutions for SOC operations


• Exposure to DevSecOps, cloud security, or modern security architectures

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