MDR - AI Security - Prisma Airs - ACON @ KPMG Global Services

We are looking for a of AI Prisma Air resource with 2 to 6 years of experience for one of our engagements. The resource must work from our Noida office and willing to work on shifts

Work experience

• 2–6 years in cloud security operations and engineering with progressive responsibility in securing enterprise cloud environments across AWS and Azure.
• Oversee enterprise-scale cloud security architecture, policy governance, and security operations across AWS and Azure environments.
• Lead implementation and management of cloud-native security controls including IAM, security groups, network segmentation, and encryption services.
• Manage day-to-day cloud security operations including monitoring, alert triage, incident response, and remediation coordination across AWS and Azure platforms.
• Drive cloud security posture improvement using CSPM tools (Wiz, Prisma Cloud, or similar); identify misconfigurations, prioritize findings, and track remediation to closure.
• Lead cross-functional teams in cloud security operations, vulnerability management, and compliance initiatives aligned with security standards.
• Drive adherence to defined SLAs and KPIs across cloud security operations; track, report, and continuously improve operational metrics and service delivery standards.
• Manage and track security incidents, service requests, and change management activities through ITSM/ticketing platforms such as ServiceNow, ensuring timely updates, escalations, and closures.
• Architect secure cloud networking solutions: design VPC/VNet topologies, implement transit gateways, Azure Firewall, AWS Network Firewall, and Network Virtual Appliances (NVAs).
• Coordinate security incident response across global teams; develop and refine playbooks, SLAs, and escalation procedures for cloud environments.
• Develop and maintain executive dashboards presenting cloud security metrics, risk posture, and compliance status to senior leadership.

The ideal candidate will

• Demonstrate solid understanding of cloud security architectures across AWS and Azure, with a strong grasp of Zero Trust principles and defense-in-depth strategies.
• Design secure cloud topologies, define security governance workflows, and guide risk-based access controls.
• Produce clear SOPs, runbooks, security assessment reports, and technical design documents for cloud environments.
• Collaborate with compliance, architecture, DevOps, and operations teams to ensure security by design.
• Drive continuous improvements via automation, Infrastructure as Code (IaC), and actionable security metrics.
• Effectively manage day-to-day security operations while balancing strategic initiatives and stakeholder expectations.
• Demonstrate ability to define, monitor, and drive SLA/KPI compliance across security operations, ensuring consistent and measurable service delivery.

Mandatory Certification Required

(At least one required; multiple strongly preferred)

Core Certifications

• AWS Certified Solutions Architect – Associate
• AZ-500 – Microsoft Certified Azure Security Engineer – Associate
• Wiz Certified Cloud Fundamentals

Preferred Advanced Certifications

• AWS Certified Security – Specialty
• Microsoft Certified: Cloud and AI Security Engineer Associate
• Certified Cloud Security Professional (CCSP)
• Certified Information Systems Security Professional (CISSP).

Technical Skills Required

Cloud Networking and Architecture

• Hands-on experience designing AWS VPC architectures: security groups, NACLs, transit gateways, VPC peering, PrivateLink, and Direct Connect.
• Proficiency with Azure Virtual Networks (VNets), NSGs, Azure Firewall, User-Defined Routes (UDRs), Application Gateway, and ExpressRoute.
• Understanding of hybrid cloud connectivity, micro-segmentation, and secure network architectures across AWS and Azure.
• Familiarity with Zero Trust architecture principles and cloud-native security design patterns.

Security Operations & Analytics

• Hands-on experience managing day-to-day cloud security operations including monitoring security alerts, triaging incidents, and coordinating remediation activities across AWS and Azure.
• Strong ability to perform security assessments, configuration reviews, and compliance checks within AWS and Azure environments.
• Experience investigating findings in cloud environments, conducting root cause analysis, and implementing preventive controls.
• Proficiency in reviewing and responding to security findings from CSPM tools (Wiz, Prisma Cloud, or similar) and ensuring timely resolution within defined SLAs.
• Experience working with ITSM/ticketing tools such as ServiceNow to log, track, prioritize, and close security incidents and service requests in line with defined SLAs and KPIs.

DevSecOps & Automation

• Familiarity with Infrastructure as Code (Terraform, CloudFormation, ARM templates) and integrating security controls into IaC pipelines.
• Understanding of CI/CD security integration, container security (Docker, Kubernetes), and API security.
• Experience with automation scripting (Python, PowerShell, Lambda, or Azure Functions) to support and improve security operations.

Behavioral / team skills

• Strong communication and stakeholder management skills, including ability to explain complex security concepts in simple terms.
• Analytical mindset with strong problem‑solving and decision‑making skills.
• High level of ownership, accountability, and attention to detail.
• Ability to handle multiple priorities in fast‑paced cloud and security environments.
• Collaborative mindset with a willingness to mentor junior team members.
• Proactive, structured, and self-driven approach to work.
• Strong documentation and presentation abilities.

Educational qualifications

• Bachelor’s degree in Computer Science, Information Technology, Information Security, Artificial Intelligence, Data Science, Engineering, or a related discipline.
• Postgraduate qualification in AI, Cybersecurity, Cloud Computing, or Information Systems is preferred.
• Equivalent relevant experience in enterprise AI or cybersecurity may be considered.

Work experience

• 2–6 years of experience in cybersecurity, cloud security, application security, AI/ML security, or related technology roles.
• Practical exposure to enterprise AI applications, generative AI services, LLM-enabled applications, AI agents, APIs, and supporting cloud environments.
• Experience discovering and inventorying sanctioned and unsanctioned AI applications, models, agents, data flows, and associated business owners.
• Experience identifying Shadow AI usage and supporting risk assessment, governance, policy enforcement, and remediation tracking.
• Hands-on exposure to inline or API-based protection for AI applications, including inspection of prompts, responses, content, URLs, and sensitive-data movement.
• Experience supporting AI application security assessments, automated scans, vulnerability reviews, or red-team exercises against AI applications and agents.
• Ability to analyse findings such as prompt injection, sensitive-data leakage, unsafe content, insecure model or API usage, and excessive agent permissions.
• Experience documenting findings, creating tickets, tracking remediation, and reporting progress against agreed SLAs and KPIs.
• Familiarity with Prisma AIRS or comparable AI security, cloud security, API security, DLP, CASB, CSPM, or CNAPP platforms is preferred.

The ideal candidate will

• Understand the enterprise AI lifecycle, from discovery and inventory through development, deployment, runtime protection, monitoring, and governance.
• Support Prisma AIRS onboarding and day-to-day operations across AI Inventory, AI Runtime Security, AI Red Teaming, AI Supply Chain Security, and related capabilities.
• Discover AI applications and Shadow AI usage, validate ownership and business purpose, classify risk, and maintain an accurate enterprise AI inventory.
• Configure or support inline, API-based, and policy-driven safeguards for AI applications without creating unnecessary disruption to business workflows.
• Execute or support AI security scans and red-team assessments, review results, validate findings, and coordinate remediation with application, cloud, SOC, and governance teams.
• Apply working knowledge of LLM and agentic-AI risks, including prompt injection, data leakage, insecure output handling, malicious content, model or supply-chain risk, and excessive agency.
• Prepare clear SOPs, runbooks, assessment reports, dashboards, and stakeholder updates.
• Work independently, manage multiple priorities, communicate clearly, and escalate risks in a timely manner.

Mandatory Certification Required

• AI certification – must have at least one recognized AI or generative-AI certification, such as Microsoft Azure AI Fundamentals (AI-900), AWS Certified AI Practitioner, Google Cloud Generative AI Leader, or an equivalent credential.
• Cloud certification – must have at least one AWS, Microsoft Azure, or Google Cloud certification at foundational or associate level.
• Palo Alto Networks certification – good to have; Prisma AIRS, Prisma Cloud, or relevant Palo Alto Networks product training/certification is preferred.
• Additional certifications such as Security+, CEH, CCSP, or CISSP are advantageous but not mandatory.

Technical Skills Required

Enterprise AI Discovery & Governance

• Understanding of enterprise AI, generative AI, LLMs, AI agents, copilots, model endpoints, plugins/tools, and common AI application architectures.
• Ability to identify, inventory, classify, and maintain records of AI applications, models, agents, datasets, owners, integrations, and business use cases.
• Knowledge of Shadow AI discovery, risk triage, acceptable-use controls, governance workflows, exception handling, and remediation tracking.

AI Application & Runtime Security

• Working knowledge of Prisma AIRS concepts including AI Inventory, AI Runtime Security, AI Red Teaming, AI Supply Chain Security, AI Gateway, and AI security posture management.
• Understanding of inline, network-intercept, API-intercept, and gateway-based protection patterns for AI applications.
• Ability to review prompts, responses, sessions, violations, policies, and security findings related to prompt injection, sensitive-data leakage, malicious URLs/content, unsafe responses, and adversarial manipulation.

AI Security Testing & Engineering

• Exposure to AI application scanning, automated red teaming, adversarial testing, model/artifact scanning, and validation of findings.
• Familiarity with OWASP Top 10 for LLM Applications, MITRE ATLAS, NIST AI RMF, secure API practices, threat modelling, and vulnerability management.
• Basic knowledge of Python, REST APIs, JSON, authentication, logging, and integration troubleshooting; familiarity with AI/ML frameworks is desirable.

Cloud, Operations & Team Skills (Good to have skill):

• Working knowledge of AWS, Microsoft Azure, or Google Cloud security services, IAM, networking, logging, encryption, and secrets management.
• Experience with SIEM, SOAR, ITSM, DLP, CASB, CSPM/CNAPP, API security, or DevSecOps tooling is preferred.
• Strong analytical, documentation, communication, stakeholder-management, ownership, and collaborative problem-solving skills.