Lead Azure AI Security Engineer

EPAM; Poland; On-site; PLN 85,000 - 110,000; Full time

Job summary

EPAM is seeking a Lead Azure AI Security Engineer to enhance security for Azure and Microsoft cloud environments. The role involves technical leadership and designing robust security architectures, collaborating with various teams, and implementing security controls effectively.

Applicants should have a Bachelor's degree in Computer Science or equivalent, alongside practical experience with Azure services. This position offers opportunities for professional growth in a fast-paced environment with innovative AI solutions.

Qualifications

• 3+ years of experience in software development.
• Hands-on experience with Microsoft Azure and its security tools.
• Familiarity with compliance frameworks such as ISO 27001 or NIST.

Responsibilities

• Design and improve security architecture across Azure environments.
• Collaborate with teams to embed security in the delivery lifecycle.
• Train team members on security practices.

Skills

Microsoft Azure services

Cloud security concepts

Scripting with PowerShell

DevOps/DevSecOps practices

AI-assisted automation

Education

Bachelor's degree in Computer Science or related field

Tools

Microsoft Sentinel

Microsoft Defender for Cloud

Terraform

Job description

We are seeking a Lead Azure AI Security Engineer to provide technical leadership and subject matter expertise in securing Azure and Microsoft cloud environments at enterprise scale.

Responsibilities

• 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 CSPM/CNAPP, Identity and Access Management, Privileged Access Management, Data Protection and Data Loss Prevention, Microsoft Defender security stack, SIEM/SOAR, Business Continuity and Disaster Recovery, DevSecOps, container and Kubernetes security and policy-as-code.
• 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 and REST APIs.
• Use AI-powered tools and agentic workflows to automate and improve security activities such as findings triage, log analysis, incident investigation support, configuration review, compliance evidence collection and vulnerability analysis.
• Design or integrate AI agents and AI-assisted automations using modern AI platforms and frameworks 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.

Requirements

• 3+ years of experience in software development.
• 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 Entra ID/Azure Active Directory, Microsoft Defender for Cloud and Microsoft Defender XDR.
• Skills 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 Active Directory, Microsoft Entra ID, Microsoft 365, Exchange Online and hybrid identity.
• Security engineering experience in at least one business or technology domain along with participation 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 and to follow, maintain and improve defined security processes.
• Practical understanding of AI‑assisted productivity and automation including building or configuring AI agents, integrating LLMs with tools, APIs and workflows, prompt engineering and using AI tools securely with awareness of sensitive data handling.
• Good communication skills and ability to explain security risks, technical decisions and remediation plans to both technical and non‑technical stakeholders.

Nice to have

• Skills in scripting and automation using PowerShell, Python, Bash, Azure CLI, Terraform or Bicep.
• Familiarity with SIEM/SOAR platforms, especially Microsoft Sentinel, KQL and Logic Apps.
• Experience with CNAPP/CSPM/CWPP/CIEM tools such as Prisma Cloud, Wiz and Orca or Lacework, Check Point CloudGuard and CrowdStrike or Tenable and Rapid7.
• Understanding of compliance frameworks such as ISO 27001, NIST and CIS Benchmarks or PCI DSS, HIPAA and HITRUST.
• Knowledge of container and Kubernetes security including AKS, container registries and image scanning.
• Familiarity with AI/LLM platforms such as Azure OpenAI, Azure AI Foundry and Microsoft Copilot Studio or Semantic Kernel, LangChain and AutoGen.
• Understanding of AI security risks including data leakage, prompt injection, excessive agency and AI supply chain risks.
• Experience implementing AI governance and secure AI usage policies aligned with frameworks such as NIST AI RMF, OWASP Top 10 for LLM Applications or ISO/IEC 42001.
• Certification: AZ-500, SC-100, SC-200 SC-300, SC-400, AZ-104 AZ-305, CISSP, CISM CISA, CCSK, CCSP, SSCP AI-900, AI-102, PL-900/PL-200.