Role & seniority
- SOAR Automation / GenAI Engineer
- Senior (5–8 years)
Stack/tools
- Microsoft Sentinel SOAR
- Azure Logic Apps (Azure services)
- GenAI/LLMs: prompt engineering, Azure OpenAI, AI agents, RAG, LLM integration
- KQL
- Scripting: Python / PowerShell
- Data/format: JSON
- Integrations via REST APIs
- Security integrations: CrowdStrike, Microsoft Defender, DLP, Threat Intelligence, ServiceNow
Top 3 responsibilities
- Design/implement SOAR workflows for incident triage, enrichment, investigation, and response
- Build and maintain REST API integrations across security tools and ServiceNow
- Develop GenAI-powered SOC use cases (alert summarization, investigation support, threat analysis, response recommendations) with validation/guardrails/audit trails
Must-have skills
- Hands-on Microsoft Sentinel SOAR
- Azure Logic Apps
- GenAI fundamentals (LLMs, prompt engineering, SOC use-case development)
- KQL, Python/PowerShell, JSON, REST APIs
- Ability to implement AI automation with human approval, validation, security guardrails, audit trails
Nice-to-haves
- Azure OpenAI, AI agents, RAG
- Experience integrating LLM outputs directly into security workflows
- Automation opportunity identification to reduce false positives and response time
Location & work type
- Noida
- 5 days office (rotational shifts)

Full Description

Job Description: SOAR Automation / GenAI Engineer – Azure Logic Apps

Experience: 5–8 Years

Location: Noida

Shift and Schedule: 5 Days office (Rotational)

Strong hands-on experience in Microsoft Sentinel SOAR, Azure Logic Apps, and security playbook development.
Design and implement automated workflows for incident triage, alert enrichment, investigation, and response.
Develop and maintain integrations with CrowdStrike, Microsoft Defender, DLP, Threat Intelligence, and ServiceNow using REST APIs.
Proficiency in KQL, Python/PowerShell, JSON, REST APIs, and Azure services.
Hands-on experience with Generative AI (GenAI), Large Language Models (LLMs), and prompt engineering.
Develop GenAI-powered SOC use cases for alert summarization, incident investigation, threat analysis, and response recommendations.
Experience with Azure OpenAI, AI agents, RAG, and LLM integration with security workflows is preferred.
Implement AI-driven automation with appropriate validation, human approval, security guardrails, and audit trails.
Identify SOC automation opportunities to reduce manual effort, false positives, and incident response time.
Collaborate with SOC teams to deliver scalable, secure, and production-ready SOAR and GenAI solutions.