[Hiring] Azure AI Security Engineer @EPAM Systems

Role Description

We are seeking an experienced Azure AI Security Engineer to provide technical leadership and subject matter expertise in securing Azure and Microsoft cloud environments at enterprise scale. In this role, you will design and implement robust security architectures while leveraging AI-powered tools and agentic workflows to enhance daily security engineering activities. You will collaborate across multiple teams to embed security into the full delivery lifecycle and contribute to the secure adoption of AI technologies.

• Provide technical leadership and subject matter expertise in securing Azure and Microsoft cloud environments at enterprise scale.
• Design, implement, and improve security architecture across Azure, Microsoft 365, Microsoft Entra ID, hybrid and multi-cloud environments, with Azure as the primary cloud platform.
• Work across key cloud security domains, including:
  • Cloud Security Posture Management/CNAPP/CSPM
  • Identity and Access Management/Microsoft Entra ID
  • Privileged Access Management
  • Data Protection and Data Loss Prevention
  • Microsoft Defender security stack
  • SIEM/SOAR and automated incident response
  • Business Continuity and Disaster Recovery
  • DevSecOps and Infrastructure as Code security
  • Container, Kubernetes, API and microservice security
  • Compliance, governance, policy-as-code and secure cloud landing zones
• Plan, design and implement security controls for cloud workloads, applications, infrastructure and data.
• Collaborate with engineering, infrastructure, development, DevOps, database, operations and compliance teams to embed security into the full delivery lifecycle.
• Support implementation and continuous improvement of Zero Trust architecture, secure authentication, conditional access, least privilege and identity protection.
• Develop and maintain automation scripts, workflows and security tooling using:
  • PowerShell
  • Python
  • Azure CLI
  • Logic Apps
  • Azure Functions
  • KQL
  • REST APIs
• Use AI-powered tools and agentic workflows to automate and improve daily security engineering activities such as:
  • Security findings triage and prioritization
  • Log analysis and alert enrichment
  • Incident investigation support
  • Configuration review
  • Compliance evidence collection
  • Security documentation generation
  • Vulnerability and misconfiguration analysis
  • Knowledge base and runbook automation
• Design or integrate AI agents and AI-assisted automations using modern AI platforms and frameworks where appropriate, while ensuring proper security, privacy and governance controls.
• Contribute to secure adoption of AI technologies by defining guardrails for data protection, access control, prompt security, model usage, auditability and human-in-the-loop processes.
• Train and support other team members on cloud security practices, security processes and AI-assisted automation approaches.

Qualifications

• Bachelor’s degree in Computer Science, Information Security, Engineering, or equivalent practical experience.
• Hands-on experience with Microsoft Azure services.
• Strong understanding of cloud security concepts, Azure architecture and enterprise-scale cloud environments.
• Practical experience with Microsoft security technologies such as Microsoft Entra ID/Azure Active Directory, Microsoft Defender for Cloud and Microsoft Defender XDR.
• Expertise in Microsoft Sentinel, Microsoft Purview and Microsoft Intune.
• Proficiency in Conditional Access, Identity Protection and Privileged Identity Management.
• Competency in Key Vault, Azure Policy and Azure Monitor/Log Analytics.
• Strong engineering background, including experience with Microsoft infrastructure and cloud solutions such as Active Directory, Microsoft Entra ID, Microsoft 365, Exchange Online and hybrid identity.
• Security engineering experience in at least one business or technology domain.
• Experience participating in at least several production projects.
• Understanding of software development lifecycle, DevOps/DevSecOps practices, cloud security assessment methodologies and secure-by-design principles.
• Ability to work closely with developers, business analysts, QA engineers, architects, project managers, infrastructure and operations teams.
• Ability to follow, maintain and improve defined security processes.
• Practical understanding of AI-assisted productivity and automation beyond basic chatbot usage, including:
  • Building or configuring AI agents
  • Automating repetitive security or engineering tasks
  • Integrating LLMs with tools, APIs, documents or workflows
  • Prompt engineering and structured prompting
  • Creating AI-assisted runbooks, scripts, queries or documentation
  • Using AI tools securely with awareness of sensitive data handling and access control
• Good communication skills and ability to explain security risks, technical decisions and remediation plans to both technical and non-technical stakeholders.

Requirements

• Experience with scripting, automation or software development using at least one of the following: PowerShell, Python, Bash, Azure CLI, Terraform, Bicep.
• Experience with SIEM/SOAR platforms, especially Microsoft Sentinel, KQL, Logic Apps and security automation playbooks.
• Experience with CNAPP/CSPM/CWPP/CIEM tools such as Microsoft Defender for Cloud, Prisma Cloud, Wiz, Orca, Lacework, Check Point CloudGuard, CrowdStrike, Tenable, Rapid7 or similar.
• Experience with Infrastructure as Code and policy-as-code tools such as Terraform, Bicep, ARM templates, Azure Policy, OPA, Checkov or tfsec.
• Understanding of at least one compliance or security framework, such as ISO 27001, NIST, CIS Benchmarks, PCI DSS, HIPAA, HITRUST, GDPR, SOX, SOC 2 or FedRAMP.
• Experience with container and Kubernetes security, including AKS, container registries, image scanning, runtime protection and network policies.
• Experience with AI/LLM platforms or frameworks such as Azure OpenAI, Azure AI Foundry, Microsoft Copilot Studio, Semantic Kernel, LangChain, AutoGen, Power Platform, Power Automate or similar.
• Understanding of AI security risks, including data leakage, prompt injection, excessive agency, insecure tool use, model governance and AI supply chain risks.
• Experience implementing AI governance, secure AI usage policies, or controls aligned with frameworks such as NIST AI RMF, OWASP Top 10 for LLM Applications or ISO/IEC 42001.

Benefits

• Security certifications such as:
  • AZ-500: Microsoft Azure Security Technologies
  • SC-100: Microsoft Cybersecurity Architect
  • SC-200: Microsoft Security Operations Analyst
  • SC-300: Microsoft Identity and Access Administrator
  • SC-400: Microsoft Information Protection Administrator
  • AZ-104: Microsoft Azure Administrator
  • AZ-305: Azure Solutions Architect Expert
  • CISSP, CISM, CISA, CCSK, CCSP, SSCP or similar
• AI-related certifications, for example:
  • AI-900: Microsoft Azure AI Fundamentals
  • AI-102: Azure AI Engineer Associate
  • PL-900 / PL-200 for Power Platform automation scenarios