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PricewaterhouseCoopers (PwC)

Global professional services: assurance, tax, consulting

Senior Cloud Engineer - Cloud Data Security, AI Integrations

Cloud EngineeringPosted on Nov 11
Full-timeBudapest, HungaryNo salary listed

About the Job

Requirements

  • At least 7 years of relevant cloud engineering experience, including active, hands-on work implementing complex platforms.
  • In-depth AWS and/or GCP knowledge, including networking, identity and access management, storage services, serverless, and container platforms.
  • Practical experience designing cloud data-security controls, especially encryption, key management, and access control.
  • Experience securely implementing API-based integrations and external service connections.
  • Experience designing or implementing centralized logging, monitoring, and observability solutions.
  • Proficiency with Infrastructure as Code tools such as Terraform or CloudFormation in AWS environments.
  • Experience creating CI/CD pipelines that support platform deployment and configuration management.
  • Ability to independently build automation using Python, Bash, or a similar language.
  • Basic knowledge of AI-agent frameworks, large language model integration patterns, or generative AI tools used in security workflows.
  • Ability to make independent technical decisions and balance security, reliability, and operational considerations.
  • Confident, work-capable English proficiency.
  • A higher-education qualification in IT, information security, data engineering, or a related field, or equivalent professional experience.

Responsibilities

  • Design, develop, support security-compliance validation for, deploy, and operate cloud-based data-security platforms and AI integrations.
  • Build secure, enterprise-scale integrations between internal systems and external AI providers.
  • Design a unified logging, monitoring, and observability architecture, with particular attention to data protection and system interoperability.
  • Implement infrastructure to receive, store, process, and support automated or manual review of security signals from AI providers.
  • Develop secure data-storage solutions and enforce encryption, key-management, and access-control requirements.
  • Develop and operate AWS- and GCP-based solutions, supporting Azure integrations as needed.
  • Use Infrastructure as Code and CI/CD to automate platform deployment, configuration management, and scaling.
  • Apply containerized and serverless solutions according to platform requirements.
  • Collaborate with AI providers, external partners, and internal cloud, data-security, and operations teams.
  • Investigate technical faults and performance problems, and prepare documentation and operational guides.

Desired Qualifications

  • Experience with architectures connecting multiple cloud providers, including AWS, GCP, or Azure.
  • Practical experience with enterprise integrations of AI providers or model-serving platforms.
  • Knowledge of workflows that support processing and reviewing AI security signals.
  • Experience in a regulated industry, especially financial services.
  • Practical experience technically implementing data-retention, auditability, and log-data access requirements.
  • Practical knowledge of cloud KMS or HSM solutions, secrets management, and key rotation.
  • In-depth knowledge of Docker and Kubernetes.
  • A cloud or cloud-security professional certification.
  • Experience with technical design, professional mentoring, and coordinating across multiple organizations.

About the Company

PricewaterhouseCoopers (PwC)

Global professional services: assurance, tax, consulting

PwC provides assurance (audit), tax, legal services, consulting and deals advisory to organisations worldwide. It uses multidisciplinary teams across accounting, advisory, technology and industry, delivered through a global network of locally established firms that collaborate with technology partners to offer AI, cloud, managed services and digital trust. PwC differentiates itself with an integrated, global-local service model and technology-enabled offerings that address complex client needs across risk, transformation, reporting and sustainability. Its goal is to help clients improve governance, efficiency and value by supporting reporting accuracy, business transformation, risk management and sustainable practices.

Company size
10,001+
Company stage
Early VC
Total funding
$3.3M
Headquarters
London, United Kingdom
Founded
1989

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