Cloud & AI Security Architect

Kyndryl

Cloud & AI Security Architect at Kyndryl transforming security measures to protect organizations. Ensuring confidentiality and safety against known and unknown threats while implementing security technologies.

Posted 7/6/2026full-timeRoma • 🇮🇹 ItalyMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

AWSAzureCloudCyber SecurityGoogle Cloud PlatformKubernetesPythonTerraform

About the role

Key responsibilities & impact

Architect and implement secure cloud foundations (landing zones, identity, network segmentation, logging pipelines, key management, secrets handling).
Engineer cloud security controls and automate compliance validation using policy-as-code where applicable.
Build AI-powered security capabilities, such as: investigation and triage copilots (SOC assistance), automated alert enrichment and case summarization, detection engineering accelerators (rule generation, tuning assistance), SOAR workflow augmentation and auto-remediation suggestions, anomaly detection and behavioral analytics on security telemetry.
Design secure GenAI architectures: RAG patterns with secure data access, model gateway controls and prompt/data protections, tenant isolation and secrets management, telemetry, monitoring, and evaluation.
Integrate enterprise security platforms (SIEM/SOAR, CNAPP/CSPM, CIEM, IAM/PAM, EDR/XDR) into cohesive architectures and automated workflows.
Develop reusable assets: reference implementations, accelerators, pipelines, and templates for repeatable delivery.
Collaborate with client teams (SOC, cloud platform, app teams) to operationalize solutions—ensuring adoption, reliability, and measurable risk reduction.
Support DevSecOps practices: secure CI/CD, IaC scanning, container security and Kubernetes guardrails.

Requirements

What you’ll need

5+ years of experience in cybersecurity and/or cloud security with strong hands-on engineering exposure.
Practical experience with AWS/Azure/GCP security services and cloud-native patterns.
Understanding of cloud logging/telemetry, encryption and key management, network security, identity and access controls.
Experience prototyping or delivering AI-enabled solutions (analytics, automation, copilots, detection acceleration).
Familiarity with RAG, embeddings, secure prompt/data handling, and AI telemetry.
Exposure to MLOps/LLMOps practices (deployment, evaluation, drift/quality monitoring, change control) is a plus.
Familiarity with SIEM/SOAR engineering, playbook design, API integrations, and workflow automation.
Scripting/engineering skills (e.g., Python) and comfort working with APIs and data pipelines.
IaC (Terraform, CloudFormation, ARM/Bicep), CI/CD integration, container/Kubernetes security exposure.
Ability to produce implementable designs (diagrams, patterns, reference implementations) and support delivery teams through build and operationalization.
Certifications (held or targeted) Cloud certifications (architect/security). Security certifications (CCSP/CCSK, CISSP, or equivalent) are a plus.

Benefits

Comp & perks

Flexible work arrangements
Professional development opportunities

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Cloud SecurityPolicy-As-CodeNetwork SecurityIdentity And Access ControlsScripting (Python)Infrastructure As Code (Terraform, CloudFormation, ARM/Bicep)Container SecurityKubernetes SecurityAI TelemetryLogging And Telemetry

Soft Skills

CollaborationProblem-SolvingCommunication

Certifications

Cloud CertificationsCCSPCCSKCISSP